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1
Harite, Shibani. "Evaluation of 10-fold cross validation and prediction error sums of squares statistic for population pharmacokinetic model validation". Scholarly Commons, 2003. https://scholarlycommons.pacific.edu/uop_etds/585.
Texto completoResumen
It was the objective of the current study to evaluate the ability of 10-fold crossvalidation and prediction error sum of squares (PRESS) statistic to identify population pharmacokinetic models (PPKM) that were estimated from data without influence observations versus PPKMs from data containing influence observations. The evaluation of 10-fold cross validation and PRESS statistic from Leave-one-out cross-validation for PPK model validation was performed in 3 Phases. In Phase 1 model parameters (theta and clearance) were estimated for datasets with and without influence observations. It was found that influence observations caused an over-estimation of the model parameters.
In Phase II the statistics from 10-fold and leave-one-out cross validation methods were used to detect models developed from influence data. The metrics of choice are RATIOK and RATIOPR statistics that can be used to identify models developed from influence data and these metrics may then find applicability across differing drugs and models. A cut-off value of 1.05 for RATIOK and RATIOPR was proposed as a discrete breakpoint to classify models that were generated from influence data versus noninfluence data.
In Phase III data analysis was carried out using logistic regression and the sensitivity and specificity of Leave-one-out and 10-fold cross-validation methods were evaluated. It was found that RATIOK and RATIOPR were significant predictors when used individually in the model. Multicollinearity was detected when RATIOK and RATIOPR were present in the model at the same time. In terms of sensitivity and specificity both 10-fold cross validation and leave-one-out cross validation showed similar performance.
2
Tillmar, Andreas. "Populations and Statistics in Forensic Genetics". Doctoral thesis, Linköpings universitet, Institutionen för klinisk och experimentell medicin, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54742.
Texto completoResumen
DNA has become a powerful forensic tool for solving cases such as linking a suspect to a crime scene, resolving biological relationship issues and identifying disaster victims. Traditionally, DNA investigations mainly involve two steps; the establishment of DNA profiles from biological samples and the interpreta-tion of the evidential weight given by theses DNA profiles. This thesis deals with the latter, with focus on models for assessing the weight of evidence and the study of parameters affecting these probability figures. In order to calculate the correct representative weight of DNA evidence, prior knowledge about the DNA markers for a relevant population sample is required. Important properties that should be studied are, for example, how frequently certain DNA-variants (i.e. alleles) occur in the population, the differences in such frequencies between subpopulations, expected inheritance patterns of the DNA markers within a family and the forensic efficiency of the DNA markers in casework. In this thesis we aimed to study important population genetic parameters that influence the weight of evidence given by a DNA-analysis, as well as models for proper consideration of such parameters when calculating the weight of evi-dence in relationship testing. We have established a Swedish frequency database for mitochondrial DNA haplotypes and a haplotype frequency database for markers located on the X-chromosome. Furthermore, mtDNA haplotype frequencies were used to study the genetic variation within Sweden, and between Swedish and other European populations. No genetic substructure was found in Sweden, but strong similari-ties with other western European populations were observed. Genetic properties such as linkage and linkage disequilibrium could be im-portant when using X-chromosomal markers in relationship testing. This was true for the set of markers that we studied. In order to account for this, we pro-posed a model for how to take linkage and linkage disequilibrium into account when calculating the weight of evidence provided by X-chromosomal analysis. Finally, we investigated the risk of erroneous decisions when using DNA in-vestigations for family reunification. We showed that the risk is increased due to uncertainties regarding population allele frequencies, consanguinity and compet-ing close relationship between the tested individuals. Additional information and the use of a refined model for the alternative hypotheses reduced the risk of making erroneous decisions. In summary, as a result of the work on this thesis, we can use mitochondrial DNA and X-chromosome markers in order to resolve complex relationship in-vestigations. Moreover, the reliability of likelihood estimates has been increased by the development of models and the study of relevant parameters affecting probability calculations.
3
Manrai, Arjun Kumar. "Statistical foundations for precision medicine". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/97826.
Texto completoResumen
Thesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references.
Physicians must often diagnose their patients using disease archetypes that are based on symptoms as opposed to underlying pathophysiology. The growing concept of "precision medicine" addresses this challenge by recognizing the vast yet fractured state of biomedical data, and calls for a patient-centered view of data in which molecular, clinical, and environmental measurements are stored in large shareable databases. Such efforts have already enabled large-scale knowledge advancement, but they also risk enabling large-scale misuse. In this thesis, I explore several statistical opportunities and challenges central to clinical decision-making and knowledge advancement with these resources. I use the inherited heart disease hypertrophic cardiomyopathy (HCM) to illustrate these concepts. HCM has proven tractable to genomic sequencing, which guides risk stratification for family members and tailors therapy for some patients. However, these benefits carry risks. I show how genomic misclassifications can disproportionately affect African Americans, amplifying healthcare disparities. These findings highlight the value of diverse population sequencing data, which can prevent variant misclassifications by identifying ancestry informative yet clinically uninformative markers. As decision-making for the individual patient follows from knowledge discovery by the community, I introduce a new quantity called the "dataset positive predictive value" (dPPV) to quantify reproducibility when many research teams separately mine a shared dataset, a growing practice that mirrors genomic testing in scale but not synchrony. I address only a few of the many challenges of delivering sound interpretation of genetic variation in the clinic and the challenges of knowledge discovery with shared "big data." These examples nonetheless serve to illustrate the need for grounded statistical approaches to reliably use these powerful new resources.
by Arjun Kumar Manrai.
Ph. D.
4
Valencia, Arboleda Carlos Felipe. "Contributions to statistical learning and its applications in personalized medicine". Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49143.
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This dissertation, in general, is about finding stable solutions to statistical models with very large number of parameters and to analyze their asymptotic statistical properties. In particular, it is centered in the study of regularization methods based on penalized estimation. Those procedures find an estimator that is the result of an optimization problem balancing out the fitting to the data with the plausability of the estimation. The first chapter studies a smoothness regularization estimator for an infinite dimensional parameter in an exponential family model with functional predictors. We focused on the Reproducing Kernel Hilbert space approach and show that regardless the generality of the method, minimax optimal convergence rates are achieved. In order to derive the asymptotic analysis of the estimator, we developed a simultaneous diagonalization tool for two positive definite operators: the kernel operator and the operator defined by the second Frechet derivative of the expected data t functional. By using the proposed simultaneous diagonalization tool sharper bounds on the minimax rates are obtained. The second chapter studies the statistical properties of the method of regularization using Radial Basis Functions in the context of linear inverse problems. The regularization here serves two purposes, one is creating a stable solution for the inverse problem and the other is prevent the over-fitting on the nonparametric estimation of the functional target. Different degrees for the ill-posedness in the inversion of the operator A are considered: mildly and severely ill-posed. Also, we study different types for radial basis kernels classifieded by the strength of the penalization norm: Gaussian, Multiquadrics and Spline type of kernels. The third chapter deals with the problem of Individualized Treatment Rule (ITR) and analyzes the solution of it through Discriminant Analysis. In the ITR problem, the treatment assignment is done based on the particular patient's prognosis covariates in order to maximizes some reward function. Data generated from a random clinical trial is considered. Maximizing the empirical value function is an NP-hard computational problem. We consider estimating directly the decision rule by maximizing the expected value, using a surrogate function in order to make the optimization problem computationally feasible (convex programming). Necessary and sufficient conditions for Infinite Sample Consistency on the surrogate function are found for different scenarios: binary treatment selection, treatment selection with withholding and multi-treatment selection.
5
Wegwarth, Odette [Verfasser]. "Statistical literacy in medicine : physicians’ and patients’ understanding of health statistics in cancer screening and prevention / Odette Wegwarth". Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2015. http://d-nb.info/1073869067/34.
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6
Shen, Yuanyuan. "Ordinal Outcome Prediction and Treatment Selection in Personalized Medicine". Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:17463982.
Texto completoResumen
In personalized medicine, two important tasks are predicting disease risk and selecting appropriate treatments for individuals based on their baseline information. The dissertation focuses on providing improved risk prediction for ordinal outcome data and proposing score-based test to identify informative markers for treatment selection. In Chapter 1, we take up the first problem and propose a disease risk prediction model for ordinal outcomes. Traditional ordinal outcome models leave out intermediate models which may lead to suboptimal prediction performance; they also don't allow for non-linear covariate effects. To overcome these, a continuation ratio kernel machine (CRKM) model is proposed both to let the data reveal the underlying model and to capture potential non-linearity effect among predictors, so that the prediction accuracy is maximized. In Chapter 2, we seek to develop a kernel machine (KM) score test that can efficiently identify markers that are predictive of treatment difference. This new approach overcomes the shortcomings of the standard Wald test, which is scale-dependent and only take into account linear effect among predictors. To do this, we propose a model-free score test statistics and implement the KM framework. Simulations and real data applications demonstrated the advantage of our methods over the Wald test. In Chapter 3, based on the procedure proposed in Chapter 2, we further add sparsity assumption on the predictors to take into account the real world problem of sparse signal. We incorporate the generalized higher criticism (GHC) to threshold the signals in a group and maintain a high detecting power. A comprehensive comparison of the procedures in Chapter 2 and Chapter 3 demonstrated the advantages and disadvantages of difference procedures under different scenarios.Biostatistics
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Yong, Florence Hiu-Ling. "Quantitative Methods for Stratified Medicine". Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:17463130.
Texto completoResumen
Stratified medicine has tremendous potential to deliver more effective therapeutic intervention to improve public health. For practical implementation, reliable prediction models and clinically meaningful categorization of some comprehensible summary measures of individual treatment effect are vital elements to aid the decision-making process and bring stratified medicine to fruitful realization. We tackle the quantitative issues involved from three fronts : 1) prediction model building and selection; 2) reproducibility assessment; and 3) stratification.
First, we propose a systematic model development strategy that integrates cross-validation and predictive accuracy measures in the prediction model building and selection process. Valid inference is made possible via internal holdout sample or external data evaluation to enhance generalizability of the selected prediction model. Second, we employ parametric or semi-parametric modeling to derive individual treatment effect scoring systems. We introduce a stratification algorithm with constrained optimization by utilizing dynamic programming and supervised-learning techniques to group patients into different actionable categories. We integrate the stratification and newly proposed prediction performance metric into the model development process. The methodologies are first presented in single treatment case, and then extended to two treatment cases. Finally, adapting the concept of uplift modeling, we provide a framework to identify the subgroup(s) with the most beneficial prospect; wasteful, harmful, and futile subgroups to save resources and reduce unnecessary exposure to treatment adverse effects. The proposals are illustrated by AIDS clinical study data and cardiology studies for non-censored and censored outcomes.
The contribution of this dissertation is to provide an operational framework to bridge predictive modeling and decision making for more practical applications in stratified medicine.Biostatistics
8
Appleton, David Robertson. "Application of statistics to medicine, particularly the study of cell proliferation". Thesis, University of Edinburgh, 1990. http://hdl.handle.net/1842/27766.
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Asar, Özgür. "Longitudinal and survival statistical methods with applications in renal medicine". Thesis, Lancaster University, 2015. http://eprints.lancs.ac.uk/75552/.
Texto completoResumen
In this thesis, we develop statistical methodology to find solutions to contemporary problems in renal research. These problems include 1) assessing the association of the underlying kidney function and the risk of survival events, 2) early detection of progression towards renal failure amongst primary care patients, and 3) long-term influences of acute kidney injury occurrences on the subsequent kidney function. Joint modelling of longitudinal and time-to-event outcome and Cox model with time-varying covariate are considered to answer the first problem. Whilst parameters are estimated by maximum likelihood (ML) using an expectation-maximisation (EM) algorithm for the former model, by partial likelihood for the latter. Results show that Cox model underestimates the association parameter between the longitudinal and survival processes, and joint models correct this. A longitudinal model with a non-stationary stochastic process is developed for the second problem. Parameters are estimated by ML using a Fisher-Scoring algorithm. Based on the results of this model, we obtain the predictive distribution of meeting the clinical guideline for detecting progression. Results show that there are patients with very high probability and emerging behaviour of progression. By these probabilities, we aim to inform clinical decision-making. Another longitudinal model with a class of stationary stochastic processes and heavy tailed response distribution is developed for the third problem. Parameters are estimated by ML using an EM algorithm, and random effects are predicted using the conditional distribution of random effects given data. Results show that AKI might have serious impacts on kidney function such that on average the loss of kidney function doubles after having an AKI. Nonetheless, there are substantial between patient heterogeneity in terms of this influence. The R package lmenssp which enables inference for a range of mixed models with non-stationary stochastic processes is developed and its core features are presented.
10
VIGNALI, GIULIA. "ANALISI STATISTICO-CRIMINOLOGICA DEGLI OMICIDI OCCORSI NEL DISTRETTO GIUDIZIARIO DI MILANO E MONZA NEGLI ANNI 2006-2021". Doctoral thesis, Università degli Studi di Milano, 2023. https://hdl.handle.net/2434/950355.
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A retrospective analysis was conducted of the homicides that occurred in the area under the jurisdiction of the Public Prosecutors of Milan and Monza and were autopsied at the Institute of Forensic Medicine of Milan between 1 January 2006 and 31 December 2021.
The data was collected from autopsy reports, interviews with the victims' families, clinical records and local newspapers.
In total, of the 11,480 autopsies performed in the period of interest, 301 were found to be attributable to voluntary homicides. 94 (31.23%) crimes occurred within the family context, and 207 (68.77%) outside.
The following were evaluated: the personal characteristics of the subjects involved (sex, age, geographical origin); the risk factors present in victims and killers; the characteristics of the event (place, modality). The results were then analyzed by differentiating and comparing the two groups (intra- and extra-family).
Statistically significant differences emerged for many of the variables analysed.
The people involved in family murders are on average older, almost always Italian and the involvement of women is greater than in the other group (although predominantly men are always involved).
Great differences also concerned risk factors: much more often those who kill outside the family context have already committed previous crimes or are involved in illicit trafficking; within the family, however, psychic pathologies such as depression prevail among the perpetrators and illness/non-self-sufficiency among the victims.
Finally, in addition to the reliable differences inherent in the place of the crime (those who kill a family member do it inside the shared house, in almost all cases), there was also a greater use of weapons (firearms or bladed weapons) in those who kill outside the family.
It can thus be assumed that homicides inside and outside the family have few points in common, and that the typology of subjects involved is substantially different.
11
Li, Qike y Qike Li. "New Statistical Methods of Single-subject Transcriptome Analysis for Precision Medicine". Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/626305.
Texto completoResumen
Precision medicine provides targeted treatment for an individual patient based on disease mechanisms, promoting health care. Matched transcriptomes derived from a single subject enable uncovering patient-specific dynamic changes associated with disease status. Yet, conventional statistical methodologies remain largely unavailable for single-subject transcriptome analysis due to the "single-observation" challenge. We hypothesize that, with statistical learning approaches and large-scale inferences, one can learn useful information from single-subject transcriptome data by identifying differentially expressed genes (DEG) / pathways (DEP) between two transcriptomes of an individual. This dissertation is an ensemble of my research work in single-subject transcriptome analytics, including three projects with varying focuses. The first project describes a two-step approach to identify DEPs by employing a parametric Gaussian mixture model followed by Fisher's exact tests. The second project relaxes the parametric assumption and develops a nonparametric algorithm based on k-means, which is more flexible and robust. The third project proposes a novel variance stabilizing framework to transform raw gene counts before identifying DEGs, and the transformation strategically by-passes the challenge of variance estimation in single-subject transcriptome analysis. In this dissertation, I present the main statistical methods and computational algorithms for all the three projects, as well as their real-data applications to personalized treatments.
12
Kim, Taiyun. "Development of statistical methods for integrative omics analysis in precision medicine". Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28838.
Texto completoResumen
Precision medicine is an integrative approach to the prevention and treatment of complex diseases such as cardiovascular disease that considers an individual’s lifestyle, clinical information, and omics profile. In the last decade, the advances in omics technologies have allowed researchers to gain insight into biological systems and progress to precision medicine. Many omics technology now enables us to rapidly generate, store and analyse data at a large scale. Many efforts have attempted to integrate large-scale multi-batch and multi-omics data. While many strategies have been developed, challenges remain in developing a robust method cap- able of pre-processing large-scale datasets, handling mislabelled information, and performing integrative analysis.
Pre-processing any omics data is essential to remove technical factors whilst preserving biological variance. However, many methods still struggle to mitigate the batch effect, particularly for protracted acquisitions. Furthermore, robust visualisation tools for processing, quality control diagnostics, and integrative analysis of omics data are still lacking in effective data visualisation and integration. Lastly, cell type annotation remains a key challenge in single-cell transcriptomic data analysis due to the incompleteness of our current knowledge and the human subjectivity involved in manual curation. Together, these may result in cell type mislabelling and potentially lead to false discoveries in downstream analysis. This thesis first introduces each of the above challenges in detail (Chapter 1). We then introduce novel strategies and robust methods for the removal of unwanted variation in large-scale metabolomics data (Chapter 2), visualisation tools for omics data diagnostics and integrative analysis (Chapter 3), and cell-type identification methods in single cell transcriptomics data (Chapter 4). Chapter 5 summarises the contributions of each chapter to precision medicine and concludes the thesis.
13
Wang, Yu Xiang. "A Statistical Framework for Incorporating Multi-Omics Technologies for Precision Medicine". Thesis, The University of Sydney, 2019. https://hdl.handle.net/2123/21814.
Texto completoResumen
This thesis addresses important statistical challenges in precision medicine, the clinical practice to customise treatment plans for individual patients using genetic information. We propose methods, frameworks and procedures that tackle the discovery, translation and implementation of precision medicine through the use of omics data. In Chapter 1, we provide a brief overview of precision medicine with a special focus on targeted assays as a potential instrument for large-scale implementation. We present an overview of the statistical challenges that must be overcome in three phases of precision medicine in order to facilitate the final implementation. Chapter 2 of this thesis focuses on adapting the classical gene-set tests for targeted assays by proposing a new method, bcGST (bias-corrected Gene Set Test). We will show how bcGST makes an improvement in cases where the gene-set selection bias is ignored. In Chapter 3 we propose a novel variable selection method, APES (APproximated Exhaustive Search), for generalised linear models (GLMs). APES is capable in approximating a genuine exhaustive search with a dramatically improved speed. We devise a comprehensive set of simulations to test APES's performance and apply it to a real targeted assay with hundreds of variables. In Chapter 4 we propose the Cross-Platform Omics Prediction (CPOP) procedure that constructs "transferable" models which possess high predictive power across multiple omics datasets with no additional manipulations on the model. CPOP models have biologically relevant features that are statistically stable with respect to between-data noise and thus improve the reproducibility of the predictions. We curate four melanoma datasets and a prospective targeted assay experiment to illustrate the novelty of CPOP. This thesis contributes to precision medicine research by developing relevant, interpretable and implementable statistical methods.
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Silva, Maria Helena Oliveira Vales da. "A importância da Medicina Dentária nas situações de violência doméstica". Master's thesis, Faculdade de Medicina da Universidade do Porto, 2007. http://hdl.handle.net/10216/22417.
Texto completoResumen
Mestrado em Ciências ForensesMaster Degree Course in Forensic Sciences
da sua localização por região anatómica. Para tal foram consultados os 10 registos dos relatórios periciais das avaliações da Clínica Médico Legal da Delegação do Porto do INML no âmbito da violência doméstica, incluindo os casos com abuso sexual. A análise descritiva efectuada sobre a distribuição da localização das lesões e sua tipologia, incidiu principalmente nas regiões relacionadas no âmbito da Medicina Dentária e do grupo Maxilo-Facial. Observou-se que a caracterização sócio-demográfica da nossa população demonstra que a vítima com maior incidência é a mulher (82%), com meia-idade, com uma profissão pertencente aos quadros não qualificados ou sem profissão activa (54,3%), em que o agressor mais frequente é o marido (46,1%). No caso dos idosos constatamos que o fenómeno é pouco significativo acima do grupo etário dos 80 anos. As lesões dentárias, manifestam-se mais nas mulheres com profissões pouco qualificadas, sendo a mais frequente a perda de uma peça dentária (82,1%), na região antero-superior. As regiões que manifestaram mais lesões foram os membros superiores com 39,5%, a face com 31,9%, seguidas da cabeça com 19,8%, do tronco com 17,6%, dos membros inferiores com 16,8% e o pescoço com 12,5%. O tipo de lesões mais frequentes é as equimoses, as escoriações, o hematoma e o edema. Verifica-se que a maior incidência das lesões ocorridas no contexto dos maus tratos físicos manifesta-se na área de observação e intervenção da Medicina Dentária, ao nível da cabeça (19,8%), face (31,9%) e pescoço (12,5%), o que demonstra a importância do papel da Medicina Dentária. Importa, salientar a actuação que estes profissionais poderão ter, quer em relação à prevenção, quer à intervenção. Apostar junto destes profissionais no máximo de informação e sensibilização sobre esta problemática, construindo uma alfabetização da responsabilidade médica, jurídica e social e promover uma maior capacidade interventiva dos profissionais de saúde oral. 11
Domestic violence transcends age, race, gender, culture, social-economical status and sexuality. It is a phenomenon of significant extent and intensity, involving multiple forms of violence (physical, sexual, psychological). The process unleashing domestic violence may evolve from words, a push, a shove or a slap in the face, escalating towards a pattern of violence. What we know for sure is that victims become stigmatized, experiencing solitude, rage, anguish, disappointment and bitterness. It was traditionally thought of as a family problem, so that healthcare services, formal control authorities and social services had doubts as to how to intervene. Nowadays, it s a problem integrating the whole of social and political concern, which contributed to a change in the dominant attitude towards this phenomenon, as well as the attitudes and position of healthcare professionals, who are frequently the first to tend to the victims by providing the necessary healthcare, guiding them and cooperating with police and judicial authorities by denouncing and supplying evidence. Victims of domestic violence do not present a specific profile, so detection must be universal in nature and it is necessary to establish individualized therapeutic plans. There is no unique answer to all the people who live with this kind of violence. Healthcare professionals may collaborate through the knowledge of community resources towards the solution of these people s needs, as well as through in-depth study of this theme. Having found that the most frequent injuries sustained in physically abusive contexts occur in the spectre of Dentistry s observation and intervention: head, face and neck, we conducted a study pertaining to understand the relevance and the relation of Dentistry to the complexity of this problem and to the dimension of the domestic violence theme. Thus, this study aimed at assessing the quantification of the typology of injuries and the distribution of their location by anatomical region. With this purpose, we consulted the records of medical examiner s reports for the domestic violence related assessments conducted in the Medical Legal Clinic of the Oporto Delegation of the National Institute of Legal Medicine, including those cases featuring sexual abuse. 12 The descriptive analysis conducted on the distribution of the injuries location and their typology was mostly focused in regions related to Dentistry and of the Jaw-Facial Group. The social-demographic characterization of our population shows a greater incidence of victims in women (82%), mostly middle-aged, with little professional qualifications or no active profession (54.3%), in which cases the most frequent offender is the husband (46.1%). In the elderly sector of the population, this phenomenon is of little significance above the 80 year old age group. Dental injuries are more present in women with low-qualification professions, the most frequent being the loss of a dental piece (82.1%), in the anterior-superior region. Those regions showing the most injuries were the superior limbs (39.5%), the face (31.9%), followed by the head (19.8%), torso (17.6%), lower limbs (16.8%) and neck (12.5%). The most frequent types of injuries are bruises, lacerations, haematoma and oedema. The greatest incidence of injuries sustained in physically abusive contexts occurs in the spectre of Dentistry s observation and intervention, affecting the head (19.8%), face (31.9%) and neck (12.5%), thus emphasizing the relevance of Dentistry s role. It matters, to point out the actuation that these professionals will be able to have, either in relation to the prevention, or to the intervention. To stimulate next to these professionals in the maximum of information and sensitization on this problematic one, constructing a Teaching of the medical, legal and social responsibility and to promote a bigger capacity intervention of the professionals of Dental medicine.
15
Silva, Maria Helena Oliveira Vales da. "A importância da Medicina Dentária nas situações de violência doméstica". Dissertação, Faculdade de Medicina da Universidade do Porto, 2007. http://hdl.handle.net/10216/22417.
Texto completoResumen
Mestrado em Ciências ForensesMaster Degree Course in Forensic Sciences
da sua localização por região anatómica. Para tal foram consultados os 10 registos dos relatórios periciais das avaliações da Clínica Médico Legal da Delegação do Porto do INML no âmbito da violência doméstica, incluindo os casos com abuso sexual. A análise descritiva efectuada sobre a distribuição da localização das lesões e sua tipologia, incidiu principalmente nas regiões relacionadas no âmbito da Medicina Dentária e do grupo Maxilo-Facial. Observou-se que a caracterização sócio-demográfica da nossa população demonstra que a vítima com maior incidência é a mulher (82%), com meia-idade, com uma profissão pertencente aos quadros não qualificados ou sem profissão activa (54,3%), em que o agressor mais frequente é o marido (46,1%). No caso dos idosos constatamos que o fenómeno é pouco significativo acima do grupo etário dos 80 anos. As lesões dentárias, manifestam-se mais nas mulheres com profissões pouco qualificadas, sendo a mais frequente a perda de uma peça dentária (82,1%), na região antero-superior. As regiões que manifestaram mais lesões foram os membros superiores com 39,5%, a face com 31,9%, seguidas da cabeça com 19,8%, do tronco com 17,6%, dos membros inferiores com 16,8% e o pescoço com 12,5%. O tipo de lesões mais frequentes é as equimoses, as escoriações, o hematoma e o edema. Verifica-se que a maior incidência das lesões ocorridas no contexto dos maus tratos físicos manifesta-se na área de observação e intervenção da Medicina Dentária, ao nível da cabeça (19,8%), face (31,9%) e pescoço (12,5%), o que demonstra a importância do papel da Medicina Dentária. Importa, salientar a actuação que estes profissionais poderão ter, quer em relação à prevenção, quer à intervenção. Apostar junto destes profissionais no máximo de informação e sensibilização sobre esta problemática, construindo uma alfabetização da responsabilidade médica, jurídica e social e promover uma maior capacidade interventiva dos profissionais de saúde oral. 11
Domestic violence transcends age, race, gender, culture, social-economical status and sexuality. It is a phenomenon of significant extent and intensity, involving multiple forms of violence (physical, sexual, psychological). The process unleashing domestic violence may evolve from words, a push, a shove or a slap in the face, escalating towards a pattern of violence. What we know for sure is that victims become stigmatized, experiencing solitude, rage, anguish, disappointment and bitterness. It was traditionally thought of as a family problem, so that healthcare services, formal control authorities and social services had doubts as to how to intervene. Nowadays, it s a problem integrating the whole of social and political concern, which contributed to a change in the dominant attitude towards this phenomenon, as well as the attitudes and position of healthcare professionals, who are frequently the first to tend to the victims by providing the necessary healthcare, guiding them and cooperating with police and judicial authorities by denouncing and supplying evidence. Victims of domestic violence do not present a specific profile, so detection must be universal in nature and it is necessary to establish individualized therapeutic plans. There is no unique answer to all the people who live with this kind of violence. Healthcare professionals may collaborate through the knowledge of community resources towards the solution of these people s needs, as well as through in-depth study of this theme. Having found that the most frequent injuries sustained in physically abusive contexts occur in the spectre of Dentistry s observation and intervention: head, face and neck, we conducted a study pertaining to understand the relevance and the relation of Dentistry to the complexity of this problem and to the dimension of the domestic violence theme. Thus, this study aimed at assessing the quantification of the typology of injuries and the distribution of their location by anatomical region. With this purpose, we consulted the records of medical examiner s reports for the domestic violence related assessments conducted in the Medical Legal Clinic of the Oporto Delegation of the National Institute of Legal Medicine, including those cases featuring sexual abuse. 12 The descriptive analysis conducted on the distribution of the injuries location and their typology was mostly focused in regions related to Dentistry and of the Jaw-Facial Group. The social-demographic characterization of our population shows a greater incidence of victims in women (82%), mostly middle-aged, with little professional qualifications or no active profession (54.3%), in which cases the most frequent offender is the husband (46.1%). In the elderly sector of the population, this phenomenon is of little significance above the 80 year old age group. Dental injuries are more present in women with low-qualification professions, the most frequent being the loss of a dental piece (82.1%), in the anterior-superior region. Those regions showing the most injuries were the superior limbs (39.5%), the face (31.9%), followed by the head (19.8%), torso (17.6%), lower limbs (16.8%) and neck (12.5%). The most frequent types of injuries are bruises, lacerations, haematoma and oedema. The greatest incidence of injuries sustained in physically abusive contexts occurs in the spectre of Dentistry s observation and intervention, affecting the head (19.8%), face (31.9%) and neck (12.5%), thus emphasizing the relevance of Dentistry s role. It matters, to point out the actuation that these professionals will be able to have, either in relation to the prevention, or to the intervention. To stimulate next to these professionals in the maximum of information and sensitization on this problematic one, constructing a Teaching of the medical, legal and social responsibility and to promote a bigger capacity intervention of the professionals of Dental medicine.
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Chan, Pui-shan y 陳佩珊. "On the use of multiple imputation in handling missing values in longitudinal studies". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B45009879.
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Luk, Yee-kam y 陸綺琴. "Traditional Chinese medicine in Hong Kong: prevalence, costs and patterns of use". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31970072.
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Plata, Santos Hector Andres. "Subgroup identification in classification scenario with multiple treatments". Thesis, Linköpings universitet, Statistik och maskininlärning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166064.
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The subgroup identification field which sometimes is called personalized medicine, tries to group individuals such that the effects of a treatment are the most beneficial for them. One of the methods developed for this purpose is called PSICA. Currently this method works in a setting of multiple treatments and real valued response variables. In this thesis, this methodology is extended to the degree that it can also handle ordinal response variables that can take a finite number of values. It is also compared to a competitor method which results in similar performance but with the added value of a probabilistic output and a model that is interpretable and ready for policy making. This is achieved at the expense of a higher execution time. Finally, this extension is applied to a longitudinal study done in Nicaragua in the los Cuatro Santos population in which some interventions were applied in order to reduce poverty. The results showed which were the most beneficial treatments for different population subgroups.
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Frison, Lars Johan. "Analysis of repeated measures in clinical trials using summary statistics". Thesis, London School of Hygiene and Tropical Medicine (University of London), 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388955.
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Piryatinska, Alexandra. "Inference for the Levy models and their application in medicine and statistical physics". Case Western Reserve University School of Graduate Studies / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=case1100206169.
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Piryatinska, Alexandra. "Inference for the Lévy models and their applications in medicine and statistical physics". online version, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1100206169.
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Luo, Dehui. "Statistical learning of median in meta-analysis". HKBU Institutional Repository, 2017. https://repository.hkbu.edu.hk/etd_oa/469.
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As one of the most recommended strategies in decision making of contemporary medicine, evidence-based medicine (EBM) is attracting more and more attention. For EBM, the scientific evidences are obtained mainly from the randomized controlled trials (RCTs), systematic review and meta-analysis. In particular, meta-analysis can help researchers statistically combine several independent studies for a same clinical problem. In meta-analysis, Cohen's d and Hedges' g are among the most commonly used effect size measurements for continuous data. To compute these mean difference criteria, the sample mean and standard deviation are two conventional statistics reported in the literature. However, some other clinical studies may instead report the median, minimum and maximum values, and/or sample quartiles. Such a situation requires researchers to estimate the sample mean and standard deviation from these reported summary statistics. We note, however, that most existing estimators in the literature have some serious limitations. For this, we propose to improve the existing methods and extend them to three frequently encountered scenarios. In this thesis, we developed the optimal sample mean estimators, the normality test statistics and the updated Cohen's d mean difference criterion for three commonly encountered scenarios in meta-analysis. In Chapter 1, we gave a brief introduction on evidence-based medicine, meta-analysis and the summary data. In Chapter 2, we introduced our optimal estimators of the sample mean under the three scenarios, respectively. In Chapter 3, we proposed several methods for testing the normality of the underlying data. And in Chapter 4, we proposed to improve the famous Cohen's d and its relevant parameters. To assess the practical performance of our newly proposed methods, we also chose a few real data at the end of each chapter as illustrating examples. Numerical results of those studies indicated that our proposed methods have satisfactory performance both in theory and in practice. Following our new methodology, we also recommended an improved procedure for medical researchers to conduct meta-analysis. For illustration, we chose a meta-analysis in Chapter 5 on the effect of phytosterols to plasma CRP level (Rocha et al., 2016) to compare the results obtained from our recommended procedure and from the original methods. The results showed that our recommended procedure may lead to distinctly different results for a same clinical problem. To conclude the thesis, we expect that our newly proposed methods can be regarded as "rules of thumb" and will soon be widely applied in meta-analysis and evidence-based medicine.
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Žuraulytė, Vaiva. "Vaistų efektyvumo statistinė analizė". Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080924_174956-30506.
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Inkstų persodinimas yra aktuali priemonė gydant inkstų ligas. Nuo inkstų ligų visame pasaulyje kenčia apie 10 % suaugusių žmonių. Vienas suaugęs žmogus iš dešimties kenčia nuo chroniškų inkstų ligų. Apie 1,5 mln. žmonių gyvybė palaikoma dializės būdu, vidutiniškai jie inkstų persodinimo laukia apie septynerius metus. Šio darbo tikslas — nustatyti ligoniams persodinto inksto atmetimo riziką, išgyvenamumo galimybes bei terapijos įtaką. Darbe buvo tiriami duomenys pasitelkiant Kaplan-Meierio išgyvenamumo analizę, Kokso regresiją, logistinę regresiją ir t.t. Iš viso buvo ištirti 604 tiriamieji, kuriems buvo persodintas inkstas ir nustatyta, kad veiksniai įtakojantys inksto atmetimą yra ligonio amžius, svoris bei kreatino kiekis tyrimo pradžioje. Kaplan-Meierio išgyvenamumo analizė parodė, kad išgyvenamumo kreivės iki inksto atmetimo nepriklauso nuo gydymo. Kokso regresijos modelis atskleidė, kad inksto atmetimas susijęs su kreatino kiekiu pradžioje, svoriu bei amžiumi. Be to, tyrimas rodo, kad kreatino kiekis pabaigoje sumažėja, taikant tiek kontrolinę, tiek gydomąją terapiją. Reikšminiai žodžiai: p-reikšmė, Šapiro–Vilko W kriterijus, Hosmerio–Lemešou kriterijus, Voldo kriterijus.Kidney transplantation is the actual measure when treating kidney diseases. Approximately 10 percents of adults are suffering from kidney diseases. One adult person from ten suffers from chronic kidney diseases. Lifes of 1,5 millions persons are supported by dialysis. They are waiting for kidney transplantation approximately seven years. The goal of this work is to determine the risk of rejection of kidney transplanted to the patients, possibilities of survival and the influence of therapy. The data were researched in the work, invoking Kaplan-Meyer survival analysis, Cox regression and the logistics regression, and so on. In total 604 studies have been researched with the transplanted kidney and it has been determined that the factors, influencing the kidney rejection are the age of the patient, weight and quantity of creatine in the beginning of the research. Kaplan-Meyer survival analysis has shown that the survival curves until kidney rejection do not depend upon the treatment. Cox regression model has revealed that the kidney rejection is related to the quantity of creatine in the beginning, weight and age. In addition, the research shows that the quantity of creatine has decreased at the end, when either treatment or control therapies were applied. Keywords: P-meaning, Shapiro & Wilk W test, Hosmer & Lemeshow test, Vold test.
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Lankton, Shawn M. "Localized statistical models in computer vision". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31644.
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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010.Committee Chair: Tannenbaum, Allen; Committee Member: Al Regib, Ghassan; Committee Member: Niethammer, Marc; Committee Member: Shamma, Jeff; Committee Member: Stillman, Arthur; Committee Member: Yezzi, Anthony. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Kirby, Alison Jill. "Statistical modelling for the precursors of cervical cancer". Thesis, University of Cambridge, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303111.
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Preston, Carrol Lesley. "Statistical models of publication basis in meta-analysis". Thesis, Queen Mary, University of London, 2000. http://qmro.qmul.ac.uk/xmlui/handle/123456789/1624.
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Objectives: To review, apply and compare existing publication bias methodology. To extend the selection model methods that adjust combined estimates and to develop models to adjust for publication bias and heterogeneity simultaneously. ' Methods: Methodologies that test for the existence of publication bias, estimate the number of missing studies, and adjust combined estimates for publication bias are reviewed. Parametric weighted distribution methodology is developed further. The existing family of distributions is extended to include a logistic function. Weight functions previously limited to modelling selection based on two-tailed p-values have been restructured for one-tailed p-values. The selection mechanism model has been developed to incorporate both p-values and precision. The model for effect size has been developed to incorporate linear predictors, so heterogeneity and publication bias can be modelled simultaneously. Data: Two systematic reviews taken from the Cochrane Library and simulation studies. Results: Methods that test for the existence of publication bias or estimate the number of missing studies are limited by the strength of their assumptions and low power. Weighted distributions offer the only way to directly assess the impact of publication bias. In data sets in which there is heterogeneity or the true treatment effect is null, modelling the selection mechanism on p-values only can lead to over-adjusted estimates and considerable variability between estimates with wide confidence intervals. Extending the selection model to include precision reduces this. It is then possible to include other covariates such as study quality or type. The effect-size model can be extended in a similar way to include linear predictors. Combination of these two models allows simultaneous consideration of the influence of publication bias and heterogeneity. Conclusions: Weighted distributions offer a flexible approach to modelling publication bias. Inclusion of precision in the selection model reduces sensitivity of the model to the shape of the selection model improving consistency of results. No selection model should be used on its own but in conjunction with others to allow a sensitivity approach
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Carroll, Melvyn Joseph. "Applications of statistical change detection to multi-temporal multi-spectral nuclear medicine image data". Thesis, City University London, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446320.
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Parascandola, Mark John. "The 'indeterminate plaintiff' : statistical evidence and the casual inference in medicine and the law". Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627117.
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Lu, Qingshu. "Statistical analysis for two-stage adaptive designs with different study endpoints /". access full-text access abstract and table of contents, 2009. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?phd-ms-b30082766f.pdf.
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Thesis (Ph.D.)--City University of Hong Kong, 2009."Submitted to Department of Management Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves 126-130)
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Sathirapongsasuti, Jarupon Fah. "Post-Genomic Approaches to Personalized Medicine: Applications in Exome Sequencing, Microbiome, and COPD". Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:11574.
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Since the completion of the sequencing of the human genome at the turn of the century, genomics has revolutionized the study of biology and medicine by providing high-throughput and quantitative methods for measuring molecular activities. Microarray and next generation sequencing emerged as important inflection points where the rate of data generation skyrocketed. The high dimensionality nature and the rapid growth in the volume of data precipitated a unique computational challenge in massive data analysis and interpretation. Noise and signal structure in the data varies significantly across types of data and technologies; thus, the context of the data generation process itself plays an important role in detecting key and oftentimes subtle signals. In this dissertation, we discuss four areas where contextualizing the data aids discoveries of disease-causing variants, complex relationships in the human microecology, interplay between gene and environment, and genetic regulation of gene expression. These studies, each in its own unique way, have helped made possible discoveries and expanded the horizon of our understanding of the human body, in health and disease.
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Tilling, Kathleen. "Statistical methods to study the incidence and outcome of stroke". Thesis, King's College London (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325332.
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Kamal, Shahid. "Some statistical aspects of child health and growth modelling in Pakistan". Thesis, University of Exeter, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.279799.
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Li, Qian. "Studies of choice behaviors in the Medicare market". [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3386697.
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Thesis (Ph.D.)--Indiana University, Dept. of Economics, 2009.Title from PDF t.p. (viewed on Jul 15, 2010). Source: Dissertation Abstracts International, Volume: 70-12, Section: A, page: 4783. Adviser: Pravin K. Trivedi.
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Mutsvangwa, Tinashe E. M. "Statistical analysis of facial landmark data for optimisation of Fetal Alcohol Syndrome diagnosis". Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/3184.
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Includes bibliographical references (leaves 100-104).This project involved the statistical analysis of facial landmark used in Fetal Alcohol Syndrome (FAS) diagnosis. FAS is a clinical condition caused by excessive maternal consumption of alcohol during pregnancy. Diagnosis of FAS depends on evidence of growth retardation, CNS neurodevelopment abnormalities, and a characteristic pattern of facial anomalies, specifically a short palpebral fissure length, smooth philtrum, flat upper lip and flat midface. The unique facial appearance associated with FAS is emphasized in diagnosis that relies, in part, on the comparison of linear measurements of facial features to population norms.
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Kay, P. H. "The surgical treatment of mitral valve disease : A statistical approach to survival". Thesis, University of Oxford, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.375174.
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Beacon, Heather J. "Statistical analysis of self-assessed quality of life in cancer clinical trials". Thesis, London School of Hygiene and Tropical Medicine (University of London), 1996. http://researchonline.lshtm.ac.uk/682265/.
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The assessment of quality of life as a primary outcome in cancer clinical trials is now almost universal. Such data are necessarily longitudinal and multidimensional, and are often severely unbalanced by missing values or early patient death. However, to date, their reporting in the applied literature has generally used simple descriptive summaries that ignore many of these complexities. Not only can these be misleading, but they generally do not allow firm conclusions to be drawn about a major endpoint. The aim of this thesis is to assess the practical application of recent developments in statistical methodology for the analysis of quality of life data collected using self assessment questionnaires within cancer clinical trials. Its emphasis is on the use of relatively simple and flexible tools that will allow more reliable and powerful inferences to be drawn from the data than is done at present. The principal statistical tools considered are random coefficient and marginal models. It is shown that these can be successfully used for the analysis of continuous, binary and ordinal responses. In particular, they offer a simple approach to the analysis of repeated multivariate outcomes and can be very easily extended to model the complex patterns of response that are often seen in following cancer treatment. In relation to the problem of censored quality of life as a result of patient death, analyses that attempt to combine the survival and quality of life endpoints in a single variable are contrasted with those that consider the two endpoints as a multivariate problem. It is shown how this latter model can provide a summary of the quality of life response conditional on patient survival that with further work should have great application to such quality of life data. Finally, the problem of intermittent missing data is reviewed. The implications of missing data for some of the analyses presented in the thesis are assessed, and two models that attempt to determine the nature of intermittent missing data are developed. It is concluded that the problem of non-ignorable intermittent missing data presents a very challenging area of further research.
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Van, Delinder Kurt William. "Higher statistical uncertainty with small pixel sizes gives higher gamma pass rates". Thesis, Wayne State University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10193739.
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Monte Carlo (MC) based dose calculation methods trade-off accuracy at the expense of computational time, which is, correlated to the user input values of statistical uncertainty and pixel spacing (1). It was first hinted by low et. al. that noise generated within either the calculated or measured plan distributions can affect the result of the plan verification by method of ‘Gamma Index Analysis’(GI) (2). The purpose of this research experiment is to investigate a possible correlation between added noise from increasing MC statistical uncertainty and increasing the odds of a plan passing the GI verification criteria. For this research experiment, we calculated 10 head and neck radiation therapy treatment plans using the MC dose calculation method within Monaco TPS. We varied the statistical uncertainty values from 5%, 3%, 1% and 0.25% and varied the voxel size values from 3mm, 2mm and 1mm. The treatment plans were then administered on an Elekta Versa linear accelerator and measured using Mapcheck dose measurement device. Each plan was evaluated for clinical pass/fail using the GI Analysis with criteria 3%/3mm and 2%/2mm. For 1 mm voxel size, 3%/3mm GI, there was an increase in average gamma pass rates from 98.91% calculated at 0.5% statistical uncertainty to 99.61% calculated at 5% statistical uncertainty. For 1 mm voxel size, 2%/2mm GI, there was an increase in average gamma pass rates from 97.02% calculated at 0.5% statistical uncertainty to 98.80% calculated at 5% statistical uncertainty. At 2 mm and 3 mm voxel sizes, there was not a clear demonstrable increase in average gamma pass rates. The experimental results conclude that the user must be careful when selecting a statistical uncertainty prior to performing a MC dose calculation. The input of a high statistical uncertainty does not lead to more points failing the GI, but paradoxically, can increase the chances that the evaluated radiation therapy plan will pass the acceptance evaluation.
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Majeke, Lunga. "Preliminary investigation into estimating eye disease incidence rate from age specific prevalence data". Thesis, University of Fort Hare, 2011. http://hdl.handle.net/10353/464.
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This study presents the methodology for estimating the incidence rate from the age specific prevalence data of three different eye diseases. We consider both situations where the mortality may differ from one person to another, with and without the disease. The method used was developed by Marvin J. Podgor for estimating incidence rate from prevalence data. It delves into the application of logistic regression to obtain the smoothed prevalence rates that helps in obtaining incidence rate. The study concluded that the use of logistic regression can produce a meaningful model, and the incidence rates of these diseases were not affected by the assumption of differential mortality.
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Peters, T. J. "A statistical investigation of risk indicators for perinatal outcome and early child development". Thesis, University of Exeter, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233830.
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Elia, Eleni. "Statistical methods in prognostic factor research : application, development and evaluation". Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7259/.
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In patients with a particular disease or health condition, prognostic factors are characteristics (such as age, biomarkers) that are associated with different risks of a future clinical outcome. Research is needed to identify prognostic factors, but current evidence suggests that primary research is of low quality and poorly/selectively reported, which limits subsequent systematic reviews and meta-analysis. This thesis aims to improve prognostic factor research, through the application, development and evaluation of statistical methods to quantify the effect of potential prognostic factors. Firstly, I conduct a new prognostic factor study in pregnant women. The findings suggest that the albumin/creatinine ratio (ACR) is an independent prognostic factor for neonatal and, in particular, maternal composite adverse outcomes; thus ACR may enhance individualised risk prediction and clinical decision-making. Then, a literature review is performed to flag challenges in conducting meta-analysis of prognostic factor studies in the same clinical area. Many issues are identified, especially between-study heterogeneity and potential bias in the thresholds (cut-off points) used to dichotomise continuous factors, and the set of adjustment factors. Subsequent chapters aim to tackle these issues by proposing novel multivariate meta-analysis methods to ‘borrow strength’ across correlated thresholds and/or adjustment factors. These are applied to a variety of examples, and evaluated through simulation, which show how the approach can reduce bias and improve precision of meta-analysis results, compared to traditional univariate methods. In particular, the percentage reduction in the variance is of a similar magnitude to the percentage of data missing at random.
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Choi, Bong-Jin. "Statistical Analysis, Modeling, and Algorithms for Pharmaceutical and Cancer Systems". Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5200.
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The aim of the present study is to develop a statistical algorithm and model associ- ated with breast and lung cancer patients. In this study, we developed several statistical softwares, R packages, and models using our new statistical approach.
In the present study, we used the five parameters logistic model for determining the optimal doses of a pharmaceutical drugs, including dynamic initial points, an automatic process for outlier detection and an algorithm that develops a graphic user interface(GUI) program. The developed statistical procedure assists medical scientists by reducing their time in determining the optimal dose of new drugs, and can also easily identify which drugs need more experimentation.
Secondly, in the present study, we developed a new classification method that is very useful in the health sciences. We used a new decision tree algorithm and a random forest method to rank our variables and to build a final decision tree model. The decision tree can identify and communicate complex data systems to scientists with minimal knowledge in statistics.
Thirdly, we developed statistical packages using the Johnson SB probability distribu- tion which is important in parametrically studying a variety of health, environmental, and engineering problems. Scientists are experiencing difficulties in obtaining estimates for the four parameters of the subject probability distribution. The developed algorithm com- bines several statistical procedures, such as, the Newtwon Raphson, the Bisection, the Least Square Estimation, and the regression method to develop our R package. This R package has functions that generate random numbers, calculate probabilities, inverse probabilities, and estimate the four parameters of the SB Johnson probability distribution. Researchers can use the developed R package to build their own statistical models or perform desirable statistical simulations.
The final aspect of the study involves building a statistical model for lung cancer sur- vival time. In developing the subject statistical model, we have taken into consideration the number of cigarettes the patient smoked per day, duration of smoking, and the age at diagnosis of lung cancer. The response variables the survival time. The significant factors include interaction. the probability density function of the survival times has been obtained and the survival function is determined. The analysis is have on your groups the involve gender and with factors. A companies with the ordinary survival function is given.
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Schmidt, Felicitas [Verfasser] y Martin [Akademischer Betreuer] Fischer. "The role of statistical literacy for scientific reasoning & argumentation in medicine / Felicitas Schmidt ; Betreuer: Martin Fischer". München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2021. http://d-nb.info/1238518664/34.
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Krause, Linda Carina [Verfasser], Fabian [Akademischer Betreuer] Theis, Fabian [Gutachter] Theis y Bernhard [Gutachter] Küster. "Statistical data integration in translational medicine / Linda Carina Krause ; Gutachter: Fabian Theis, Bernhard Küster ; Betreuer: Fabian Theis". München : Universitätsbibliothek der TU München, 2020. http://d-nb.info/1209269740/34.
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Buckingham-Jeffery, Elizabeth. "Mathematical and statistical challenges for the surveillance of gastroenteritis". Thesis, University of Warwick, 2018. http://wrap.warwick.ac.uk/101938/.
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Gastroenteritis, causing vomiting and diarrhoea, is very common all over the world. Viral causes, such as norovirus and rotavirus, are the most frequent, although some bacteria, parasites and fungi can also lead to gastroenteritis. Many countries operate surveillance systems of diseases, including gastroenteritis or specific gastroenteritis causing pathogens. Typically, statistical methods are used to analyse surveillance data and alert public health authorities of unexpectedly high levels of illness. These methods use historical data to predict the expected value of current data. In this thesis, we address some of the challenges that remain when analysing gastroenteritis surveillance data, with a particular focus on syndromic surveillance data. We work with both mechanistic and statistical modelling approaches in an attempt to bridge the gap between the statistical methods that are used in practice for syndromic surveillance and mechanistic models that are used to model infectious diseases. In particular, we address three challenges. In chapter 2 we present a flexible framework for deriving approximations of stochastic mechanistic models of epidemics for fast inference. In chapter 3 we investigate day of the week and public holiday effects in syndromic indicators of gastroenteritis from syndromic surveillance systems operated by Public Health England in order to improve existing surveillance methodologies. In chapter 4 we identify and analyse additional online datasets for gastroenteritis, and in particular norovirus, surveillance.
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GIUDICI, FABIOLA. "Metodi statistici per la stima di profili di rischio personalizzati basati sulla medicina di precisione del cancro nei pazienti oncologici". Doctoral thesis, Università degli studi di Padova, 2022. http://hdl.handle.net/11577/3458751.
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Precision medicine is beginning to emerge as a well-defined discipline with specific goals, areas of focus, and tailored methodology. Specifically, the primary goal is to discover treatment rules that leverage heterogeneity to improve clinical decision making in a manner that is reproducible, generalizable, and adaptable as needed. This endeavor spans a broad range of scientific areas including drug discovery, genetics/genomics, health communication, and causal inference, all in
support of evidence-based, i.e., data-driven, decision making. Precision Medicine allows patients to be discriminated according to their level of risk (e.g. low or high) and identifies subgroups of patients according to their characteristics in order to assign the treatment to those who are likely to benefit. Statistics research in precision medicine is broadly focused on methodological development for estimation of and inference for treatment regimens that maximize some cumulative clinical outcome. The process for using statistical inference to establish personalized treatment strategies
requires specific techniques for data-analysis that optimize the combination of competing therapies
with candidate genetic features and characteristics of the patient and disease.
The present dissertation focuses on the implementation and application of statistical methods for
establishing optimal treatment rules for personalized medicine and discuss specific examples in
various medical contexts with oncology as an emphasis. I have focused my research activity mainly
in the study of the following topics.
1) Statistical methods to analyze continuous biomarkers.
Several approaches were considered according to the design of study: from classical approach - median or mean value, percentiles, optimal cut-point identified by means standard receiver operating characteristic (ROC) analysis-to more complex analysis - time-dependent ROC, conditional inferential tree and subpopulation Treatment Effect Pattern (STEPP) method.
2) Statistical methods for time-to-event endpoints.
Competing risks occur commonly in medical research. In the analysis of competing risks data, methods of standard survival analysis lead to incorrect and biased results. In the presence of competing risks, data analysis has to be performed including methods to calculate the cumulative incidence of an event of interest, to compare cumulative incidence curves in the presence of competing risks, and to perform competing risks regression analysis.
3) Meta-analysis for synthesizing evidence.
4) An important topic reviews to use of several statistical methods that handle the issue of treatment switching. The contribution aims at assessing tamoxifen treatment effect taking into account treatment switches, in order to provide a robust assessment of treatment effect applying causal inference methods.
5) The last topic deals with the use of population-based registry and administrative databases.
The objective of this project is to develop an acceptable claims-based algorithm to identify second breast cancer events during a 10-year follow-up through a record-linkage of two data sources:the Friuli Venezia Giulia population based-cancer registry and the administrative individual-record FVG database.Precision medicine is beginning to emerge as a well-defined discipline with specific goals, areas of focus, and tailored methodology. Specifically, the primary goal is to discover treatment rules that leverage heterogeneity to improve clinical decision making in a manner that is reproducible, generalizable, and adaptable as needed. This endeavor spans a broad range of scientific areas including drug discovery, genetics/genomics, health communication, and causal inference, all in support of evidence-based, i.e., data-driven, decision making. Precision Medicine allows patients to be discriminated according to their level of risk (e.g. low or high) and identifies subgroups of patients according to their characteristics in order to assign the treatment to those who are likely to benefit. Statistics research in precision medicine is broadly focused on methodological development for estimation of and inference for treatment regimens that maximize some cumulative clinical outcome. The process for using statistical inference to establish personalized treatment strategies requires specific techniques for data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics of the patient and disease. The present dissertation focuses on the implementation and application of statistical methods for establishing optimal treatment rules for personalized medicine and discuss specific examples in various medical contexts with oncology as an emphasis. I have focused my research activity mainly in the study of the following topics. 1) Statistical methods to analyze continuous biomarkers. Several approaches were considered according to the design of study: from classical approach - median or mean value, percentiles, optimal cut-point identified by means standard receiver operating characteristic (ROC) analysis-to more complex analysis - time-dependent ROC, conditional inferential tree and subpopulation Treatment Effect Pattern (STEPP) method. 2) Statistical methods for time-to-event endpoints. Competing risks occur commonly in medical research. In the analysis of competing risks data, methods of standard survival analysis lead to incorrect and biased results. In the presence of competing risks, data analysis has to be performed including methods to calculate the cumulative incidence of an event of interest, to compare cumulative incidence curves in the presence of competing risks, and to perform competing risks regression analysis. 3) Meta-analysis for synthesizing evidence. 4) An important topic reviews to use of several statistical methods that handle the issue of treatment switching. The contribution aims at assessing tamoxifen treatment effect taking into account treatment switches, in order to provide a robust assessment of treatment effect applying causal inference methods. 5) The last topic deals with the use of population-based registry and administrative databases. The objective of this project is to develop an acceptable claims-based algorithm to identify second breast cancer events during a 10-year follow-up through a record-linkage of two data sources:the Friuli Venezia Giulia population based-cancer registry and the administrative individual-record FVG database.
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Herrmann, Irene. "Influences of statistical analysis on result presentations of oral implant treatment /". Göteborg : Department of Oral and Maxillofacial Surgery, Sahlgrenska akademin, Göteborgs universitet, 2007. http://hdl.handle.net/2077/4433.
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Cerqueira, Joana Isabel da Cruz Santos Rodrigues. "Frequência de portadores para a Ataxia de Friedreich em Portugal: considerações éticas e legais sobre o papel da medicina preditiva na prevenção de doenças genéticas". Master's thesis, Faculdade de Medicina da Universidade do Porto, 2006. http://hdl.handle.net/10216/22396.
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Cerqueira, Joana Isabel da Cruz Santos Rodrigues. "Frequência de portadores para a Ataxia de Friedreich em Portugal: considerações éticas e legais sobre o papel da medicina preditiva na prevenção de doenças genéticas". Dissertação, Faculdade de Medicina da Universidade do Porto, 2006. http://hdl.handle.net/10216/22396.
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Zhang, Lin Tubbs Jack Dale. "Semiparametric AUC regression for testing treatment effect in clinical trial". Waco, Tex. : Baylor University, 2008. http://hdl.handle.net/2104/5237.
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Reinkemeyer, Steven. "Network vulnerability assessments : a proactive approach to protecting Naval medicine information assets /". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Jun%5FReinkemeyer.pdf.
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Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, June 2004.Thesis advisor(s): Scott Cote, Dan C. Boger. Includes bibliographical references (p. 67-71). Also available online.