Дисертації з теми "Real word Data"
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Rodittis, Katherine, and Patrick Mattingly. "USING MICROSOFT’S COMPONENT OBJECT MODEL (COM) TO IMPROVE REAL-TIME DISPLAY DEVELOPMENT FOR THE ADVANCED DATA ACQUISITION AND PROCESSING SYSTEM (ADAPS)." International Foundation for Telemetering, 2000. http://hdl.handle.net/10150/606801.
Повний текст джерелаMicrosoft’s Component Object Model (COM) allows us to rapidly develop display and analysis features for the Advanced Data Acquisition and Processing System (ADAPS).
Anantharajah, Kaneswaran. "Robust face clustering for real-world data." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/89400/1/Kaneswaran_Anantharajah_Thesis.pdf.
Повний текст джерелаAllen, Brett. "Learning body shape models from real-world data /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/6969.
Повний текст джерелаApeh, Edward Tersoo. "Adaptive algorithms for real-world transactional data mining." Thesis, Bournemouth University, 2012. http://eprints.bournemouth.ac.uk/20989/.
Повний текст джерелаNaulleau, Patrick. "Optical signal processing and real world applications /." Online version of thesis, 1993. http://hdl.handle.net/1850/12136.
Повний текст джерелаVogetseder, Georg. "Functional Analysis of Real World Truck Fuel Consumption Data." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1148.
Повний текст джерелаThis thesis covers the analysis of sparse and irregular fuel consumption data of long
distance haulage articulate trucks. It is shown that this kind of data is hard to analyse with multivariate as well as with functional methods. To be able to analyse the data, Principal Components Analysis through Conditional Expectation (PACE) is used, which enables the use of observations from many trucks to compensate for the sparsity of observations in order to get continuous results. The principal component scores generated by PACE, can then be used to get rough estimates of the trajectories for single trucks as well as to detect outliers. The data centric approach of PACE is very useful to enable functional analysis of sparse and irregular data. Functional analysis is desirable for this data to sidestep feature extraction and enabling a more natural view on the data.
Langdell, Stephen James. "Radial basis function networks for modelling real world data." Thesis, University of Huddersfield, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285590.
Повний текст джерелаTsapeli, Theofania Kleio. "Understanding real-world phenomena from human-generated sensor data." Thesis, University of Birmingham, 2018. http://etheses.bham.ac.uk//id/eprint/8445/.
Повний текст джерелаSaunders, L. J. "Studies on real world visual field data in glaucoma." Thesis, City, University of London, 2015. http://openaccess.city.ac.uk/16170/.
Повний текст джерелаLövenvald, Frans-Lukas. "FINDING ANOMALOUS TIME FRAMES IN REAL-WORLD LOG DATA." Thesis, Umeå universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163311.
Повний текст джерелаLarsson, Daniel. "ARAVQ for discretization of radar data : An experimental study on real world sensor data." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11114.
Повний текст джерелаNagao, Katashi, Katsuhiko Kaji, and Toshiyuki Shimizu. "Discussion Mining : Knowledge Discovery from Data on the Real World Activities." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2004. http://hdl.handle.net/2237/10350.
Повний текст джерелаParker, K. N. "Numeric data frames and probabilistic judgments in complex real-world environments." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1536437/.
Повний текст джерелаTreitz, Bastian. "Comparison of data-communication technologies for a Real-World Business Application." Hochschule für Technik, Wirtschaft und Kultur, 2020. https://htwk-leipzig.qucosa.de/id/qucosa%3A73720.
Повний текст джерелаNogueira, Mariana. "Machine learning to support exploring and exploiting real-world clinical longitudinal data." Doctoral thesis, Universitat Pompeu Fabra, 2020. http://hdl.handle.net/10803/669968.
Повний текст джерелаEl seguimiento de la evolución de un paciente tomando las mismas medidas en diferentes instantes temporales (datos longitudinales) es un componente crucial en la dinámica de los cuidados médicos, ya que permite tomar decisiones correctas en el momento idóneo para prevenir eventos adversos. Es entonces importante que los médicos tengan a su disposicion herramientas para analizar datos de carácter longitudinal. Sin embargo, la mayoría de las herramientas que actualmente existen tienen una aplicabilidad limitada si los datos (1) no están suficientemente estandarizados o (2) son muy heterogéneos (eg: imágenes, señales, variables continuas y categóricas) y/o tienen una alta dimensionalidad. Estas limitaciones son tremendamente relevantes, ya que ambos casos son prevalentes en la practica clínica habitual. El objetivo de esta tesis es el desarrollo de herramientas que facilitan la integración e interpretación de datos clínicos longitudinales que son complejos y no están estandarizados. Específicamente, exploramos enfoques basados en la reducción de dimensionalidad no supervisada, que permite integrar datos longitudinales complejos y su representación como una trayectoria de baja dimensión que es clínicamente interpretable. Mostramos el potencial del enfoque propuesto en el contexto de dos problemas clínicos en diferentes ámbitos y con diferentes desafíos: (1) ecocardiografía de estrés no estandarizada y (2) monitoreo de parto y toma de decisiones. En la primera aplicación, el enfoque propuesto ha mostrado ser de ayuda en la identificación de patrones normales y anormales en la respuesta cardiaca al estrés y en entender los mecanismos patofisiologicos subyacentes, en el contexto de una adquisición de datos longitudinales no estandarizados que contiene un flujo de datos heterogéneo. En la segunda aplicación, mostramos como el enfoque propuesto puede ser el concepto central de un sistema de monitoreo del parto y soporte a la decisión personalizado, superando el sistema actual de referencia. En conclusión, creemos que esta tesis muestra que la reducción de dimensión no supervisada es un prometedor enfoque para analizar datos clínicos longitudinales complejos y no estandarizados.
Hu, Yang. "PV Module Performance Under Real-world Test Conditions - A Data Analytics Approach." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1396615109.
Повний текст джерелаLundmark, Lukas. "Synthetic Meta-Learning: : Learning to learn real-world tasks with synthetic data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264919.
Повний текст джерелаMetainlärning är en metodik inom maskininlärning som gör det möjligt att lära en modell nya uppgifter med endast en handfull mängd träningsexempel. Metainlärning kräver dock en stor mängd träningsdata under själva metaträningsfasen, vilket begränsar de domäner där metodiken kan användas. Detta examensarbete utreder huruvida syntetisk bilddata, som genererats med hjälp av en simulator, kan ersätta verklig bilddata under metainlärningsfasen. Metoden har utvärderats på militär fordonsklassificering. Resultaten visar att för bildklassificering med 1–10 träningsexempel per klass kan en modell metainlärd med syntetisk data närma sig prestandan hos en modell metainlärd med riktig data. Resultaten visar även att små ändringar i genereringsprocessen, exempelvis graden av slumpmässigt ljus, har en stor inverkan på den slutgiltiga prestandan, vilket ger hopp om att ytterligare finjustering av genereringsprocessen kan resultera i ännu fler prestandaförbättringar.
POLLINI, RAMA. "Data exploitation at different levels for Behaviour Analysis in real-world scenarios." Doctoral thesis, Università Politecnica delle Marche, 2018. http://hdl.handle.net/11566/253152.
Повний текст джерелаThe research was carried out in the field of behavioural analysis, with the aim of exploiting and re-elaborating different types of data, offering the basis for new developments and methodologies within a given scenario. The analysis of behaviour has been addressed in 3 real-life scenarios. In Ambient Assisted Living (AAL) has been created an architecture based on the "Zabbix" platform that can monitor and collect data from different smart objects in a home automation house. In this context, the main objective was to exploit the data collected to define and outline anomalous behaviours of elderly people in their homes, implementing an intelligent system based on machine learning algorithms capable of triggering alarms; an innovative aspect of this system is the ability to cross alarms from multiple SOs ensuring a decrease in false positives. The project involved 16 companies and 2 universities. In Industry 4.0, an application has been developed for augmented reality, usable through smart glasses and aimed at training on the job. The project stems from the collaboration of Intermac, a company specialized in stone, glass and metal processing. The goal is to train the operator in carrying out a task by means of 3D animations and informative labels. Considerable attention has been paid to the study of wearable devices' usability because it is one of the main critical aspects of this technology. In the field of E-commerce, a study has been conducted on the navigation data of users who have made purchases within the e-commerce website. These data, suitably filtered and grouped in navigation sessions, allow to train neural networks (Long Short Term Memory networks – usually just called “LSTMs") in the recognition of action sequences. The main objective is to improve the user's purchasing process by proposing products based on the operations carried out on the e-commerce portal. The work presented in this thesis was made possible thanks to the collaboration with the IT company Apra Spa which co-financed the doctorate with a EUREKA scholarship.
Pagliarani, Andrea <1990>. "Big Data mining and machine learning techniques applied to real world scenarios." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amsdottorato.unibo.it/8904/1/Pagliarani_Andrea_tesi.pdf.
Повний текст джерелаEfendic, Nedim. "Creating a Digital Twin by Using Real World Sensors." Thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-92249.
Повний текст джерелаKenny, Ian Duncan. "An evaluation of performance enhancements to particle swarm optimisation on real-world data." Thesis, Open University, 2016. http://oro.open.ac.uk/47999/.
Повний текст джерелаPereira, Gina Ribeiro. "Real-world data as a tool for establishing the value of a medicine." Master's thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/15417.
Повний текст джерелаNos últimos anos tem sido discutido em que medida são fornecidos dados suficientes para estimar o valor clínico do medicamento durante o processo de aprovação e autorização de introdução no mercado (AIM). Apesar dos ensaios clínicos randomizados (ECR) possuírem extrema validade interna na avaliação da segurança e eficácia de novos produtos, não permitem a extrapolação dos dados de eficácia para a vida real (efetividade). Alguns peritos têm discutido o potencial uso dos dados recolhidos na vida real (DVR) na contribuição de uma avaliação mais robusta de produtos e resultados em saúde. Os avanços nas tecnologias da informação permitem recolher, partilhar, analisar e utilizar grandes quantidades de informação a um custo relativamente baixo. Neste contexto, os DVR podem ser usados em conjunto com ECR e outros dados médicos para proporcionar perspectivas sobre resultados clínicos reais. Se esses dados e metodologias puderem ser canalizados para a pré- AIM, os titulares serão capazes de direccionar o desenvolvimento de medicamentos para áreas onde o valor é susceptível de ser elevado para os doentes e sistemas de saúde. Assim, as agências regulamentares e de avaliação de tecnologias da saúde terão informação suficiente para tomar decisões devidamente fundamentadas sobre a eficácia relativa de novas intervenções em saúde. O principal objetivo desta tese é promover uma análise da utilidade dos DVR, como criadores de valor, em todas as fases de desenvolvimento de medicamentos e discutir o papel-chave de todas as partes interessadas no uso de DVR.
It has long been discussed to which extend the licensing procedure should assure the availability of sufficient data to assess the clinical value of a new dug at the time of marketing introduction. Despite the high internal validity of randomised clinical trials (RCTs) generated evidence and its ability to robustly indicate the safety and efficacy of new products, it falls short of allowing for extrapolation from efficacy to clinical effectiveness. A number of analysts and academics have signalled the potential of real-world data (RWD) to contribute to improved health products and outcomes. Advances in computing allow collecting, share, analyse and use large quantities of data routinely at a relatively low cost. In this context, RWD can be used in conjunction with RCTs and other medical data to provide insights into real-world clinical outcomes. If such data and methodologies could be harnessed in pre-authorisation drug development, drug manufactures would be able to direct drug development to areas where value is likely to be highest for patients and health systems. In addition, regulatory and Heath Technology Assessment (HTA) agencies would be able to make better-informed decisions on relative effectiveness of new health interventions. The main goal of this thesis is to analyse the usefulness of RWD collection, as creator of value, in all drug development phases and discuss the key role of all stakeholders in use of RWD.
REA, FEDERICO. "Monitoring and assessing diagnostic-therapeutic paths with healthcare utilization databases: experiences, concerns and challenges." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2020. http://hdl.handle.net/10281/262324.
Повний текст джерелаThe aim of this thesis is to provide the methodology used to develop and validate population-based prognostic scores, and to assess the effectiveness and cost-effectiveness of the diagnostic-therapeutic path of diabetes, using the healthcare utilization databases (or administrative databases) of Italian regions. Thus, the thesis is structured into the following three main parts. First, the reasons to justify the need of real-world studies in addition to evidence from randomized controlled trials, the definitions of real-world data and real-world evidence, and an overview of the Italian healthcare utilization databases are given. Second, because patients should be monitored according to their risk to experience adverse outcomes (e.g., all-cause mortality, hospital admissions), prognostic scores could be used. However, the main limitation in the use of pre-existing score is that they are usually developed in countries different from Italy and from hospital-based or pharmacy-based surveys, so hindering their applicability to all beneficiaries of the National Health Service. Therefore, two population-based prognostic scores were developed and validated using data from some Italian regions. The usefulness of one of these scores (i.e., the so-called Multisource Comorbidity Score) in the risk adjustments and as a tool for health policy planning is also shown. Third, tracing the work carried out from the “Monitoring and assessing care pathways” working group of the Italian Ministry of Health, a description of the following activities is provided: I. the development of process indicators to monitor and assess the quality of care of patients suffering from some chronic disease; II. the comparison of care quality between regions; III. the validation of the diabetes care indicators with respect to selected outcomes (i.e., the assessment of their effectiveness); IV. the assessment of the costs from the National Health Service perspective (calculated by the amount that the Regional Health Authority reimbursed to health providers) according to different levels of adherence to the diagnostic-therapeutic path of diabetes. Finally, the Beaver® regional research platform, able to compute the set of process and outcome indicators defined by the Health Ministry and to generate evidence on effectiveness and cost-effectiveness profile, is described.
Koskimäki, H. (Heli). "Utilizing similarity information in industrial applications." Doctoral thesis, University of Oulu, 2009. http://urn.fi/urn:isbn:9789514290398.
Повний текст джерелаAlmay, Felix, and Oskar Strömberg. "Applicability of Constraint Solving and Simulated Annealing to Real-World Scale University Course Timetabling Problems." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259761.
Повний текст джерелаUniversitetsschemaläggningsproblemet går ut på att skapa ett schema för universitetskurser under vissa villkor. Beslutsversionen av detta optimeringsproblem är NP-fullständig. Vi har undersökt problemet och implementerat heuristiken simulerad härdning. Denna har jämförts med avseende på tid med villkorsprogrammeringslösaren CPSolver, som är baserad på iterativ framåtsökning. Våra resultat visar att CPSolver skalar bättre för stora probleminstanser. Simulerad härdning som implementerad av oss är därför inte i sig lämplig för att generera giltiga lösningar till verklighetstrogna probleminstanser.
Franquet, Bonet Álvaro. "Statistical methods to manage and analyse real world data. Development of a health observatory in Alt Empordà. Mètodes estadístics per gestionar i analitzar real world data. Desenvolupament d'un observatori de salut a l'Alt Empordà." Doctoral thesis, Universitat de Girona, 2021. http://hdl.handle.net/10803/673830.
Повний текст джерелаAquesta tesi té com a objectiu aprofundir en el procés de creació d'un observatori de salut pública i el tractament de la informació necessària per a la presa de decisions territorials a la comarca de l'Alt Empordà. El resultat ha estat la creació d'Indika pol de salut i social de l'Alt Empordà. Indika és un observatori de salut pública que actua com a agent de salut i benestar del territori. L'objectiu d'Indika és generar coneixement sobre l'impacte dels determinants socials de salut a l'Alt Empordà. Per a això fa ús d'un marc de treball basat en tres punts: informar, conversar i actuar. Aquest marc de treball s'ha concretat en la generació de visualitzacions d'informació com infografies, col·leccions d'indicadors i una aplicació web amb l'objectiu de donar a conèixer les problemàtiques del territori i iniciar així un debat amb els diferents actors polítics i socials que permeti concretar accions de millora. En aquesta tesi, a més de la creació d'un observatori de salut pública, s'han desenvolupat dues línies d'investigació paral·leles que són: la creació d'estructures públiques d'emmagatzematge d'informació i l'anàlisi de l'arquitectura basada en esdeveniments com a forma d'estructurar la informació mèdica. Aquestes dues línies d'investigació s'han concretat en la creació de "Indika Data Repository", un repositori d'informació sobre la comarca de l'Alt Empordà a través de la plataforma col·laborativa GitHub i la implementació de la llibreria eventr en el llenguatge de programació R publicada actualment al Comprehensive R Archive Network. Eventr és una llibreria que té com a objectiu facilitar la implementació d'arquitectures basades en esdeveniments
Programa de Doctorat en Biologia Molecular, Biomedicina i Salut
Tsoi, Ada. "The Potential of Event Data Recorders to Improve Impact Injury Assessment in Real World Crashes." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/73805.
Повний текст джерелаPh. D.
GARBARINO, DAVIDE. "Acknowledging the structured nature of real-world data with graphs embeddings and probabilistic inference methods." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1092453.
Повний текст джерелаAlbrecht, Philipp, Ingrid Kristine Bjørnå, David Brassat, Rachel Farrell, Peter Feys, Jeremy Hobart, Michael Linnebank, et al. "Prolonged-release fampridine in multiple sclerosis: clinical data and real-world experience. Report of an expert meeting." Sage, 2018. https://tud.qucosa.de/id/qucosa%3A35544.
Повний текст джерелаIwao, Tomohide. "A Methodology of Dataset Generation for Secondary Use of Health Care Big Data." Kyoto University, 2020. http://hdl.handle.net/2433/253411.
Повний текст джерелаHwang, Yuan-Chun. "Local and personalised models for prediction, classification and knowledge discovery on real world data modelling problems." Click here to access this resource online, 2009. http://hdl.handle.net/10292/776.
Повний текст джерелаReinartz, Thomas [Verfasser]. "Focusing solutions for data mining : analytical studies and experimental results in real world domains / T. Reinartz." Berlin, 1999. http://d-nb.info/965635090/34.
Повний текст джерелаLai, Daphne Teck Ching. "An exploration of improvements to semi-supervised fuzzy c-means clustering for real-world biomedical data." Thesis, University of Nottingham, 2014. http://eprints.nottingham.ac.uk/14232/.
Повний текст джерелаHu, Yang. "Temporal Change in the Power Production of Real-world Photovoltaic Systems Under Diverse Climatic Conditions." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1481295879868785.
Повний текст джерелаPang, Shih-Hao. "Life Cycle Inventory Incorporating Fuel Cycle and Real-World In-Use Measurement Data for Construction Equipment and Vehicles." NCSU, 2008. http://web.lib.ncsu.edu/theses/available/etd-12152007-080346/.
Повний текст джерелаCattenoz, Mathieu. "MIMO Radar Processing Methods for Anticipating and Preventing Real World Imperfections." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112077/document.
Повний текст джерелаThe MIMO radar concept promises numerous advantages compared to today's radar architectures: flexibility for the transmitting beampattern design - including wide scene illumination and fine resolution after processing - and system complexity reduction, through the use of less antennas and the possibility to transfer system control and calibration to the digital domain. However, the MIMO radar is still at the stage of theoretical concept, with insufficient consideration for the impacts of waveforms' lack of orthogonality and system hardware imperfections.The ambition of this thesis is to contribute to paving the way to the operational MIMO radar. In this perspective, this thesis work consists in anticipating and compensating the imperfections of the real world with processing techniques. The first part deals with MIMO waveform design and we show that phase code waveforms are optimal in terms of spatial resolution. We also exhibit their limits in terms of sidelobes appearance at matched filter output. The second part consists in taking on the waveform intrinsic imperfections and proposing data-dependent processing schemes for the rejection of the induced residual sidelobes. We develop an extension for the Orthogonal Matching Pursuit (OMP) that satisfies operational requirements, especially localization error robustness, low computation complexity, and nonnecessity of training data. The third part deals with processing robustness to signal model mismatch, especially how it can be prevented or anticipated to avoid performance degradation. In particular, we propose a digital method of transmitter phase calibration. The last part consists in carrying out experiments in real conditions with the Hycam MIMO radar testbed. We exhibit that some unanticipated encountered distortions, even when limited at the matched filter output, can greatly impact the performance in detection of the data-dependent processing methods
Yogeswaran, Arjun. "Self-Organizing Neural Visual Models to Learn Feature Detectors and Motion Tracking Behaviour by Exposure to Real-World Data." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37096.
Повний текст джерелаSchirber, Sebastian, Daniel Klocke, Robert Pincus, Johannes Quaas, and Jeffrey L. Anderson. "Parameter estimation using data assimilation in an atmospheric general circulation model: Parameter estimation using data assimilation in an atmosphericgeneral circulation model: from a perfect toward the real world." American Geophysical Union (AGU), 2013. https://ul.qucosa.de/id/qucosa%3A13463.
Повний текст джерелаNguyen, Thi Yen Lien, Trung Dung Nghiem, and Minh Quý Cao. "Impact of the driving cycle on exhaust emissions of buses in Hanoi." Technische Universität Dresden, 2016. https://tud.qucosa.de/id/qucosa%3A32626.
Повний текст джерелаTóm tắt: Tác động của chu trình lái tới sự phát thải của xe buýt tại Hà Nội đã được trình bày trong bài báo này. Một chu trình lái đặc trưng của xe buýt Hà Nội đã được xây dựng dựa trên dữ liệu hoạt động ngoài thực tế của phương tiện, và chu trình lái này cũng đã được đánh giá có sự phù hợp rất cao với dữ liệu lái ngoài thực tế. Chu trình lái đặc trưng và chu trình thử ETC-part1 được sử dụng để đánh giá phát thải của phương tiện theo các chu trình lái khác nhau. Các kết quả đạt được cho thấy mức độ phát thải CO, VOC, PM, CO2 và NOx của xe buýt rất khác nhau giữa hai chu trình lái, đặc biệt là CO2 và NOx. Do đó, bài báo khẳng định sự cần thiết phải xây dựng chu trình lái đặc trưng trước khi thực hiện kiểm kê phát thải đối với nguồn động.
Leroy, Mélanie. "Contribution des bases de données de soin courant à l’amélioration du diagnostic et du pronostic de la maladie d’Alzheimer et des dégénérescences lobaires frontotemporales." Electronic Thesis or Diss., Université de Lille (2018-2021), 2021. http://www.theses.fr/2021LILUS026.
Повний текст джерелаBiomarkers, whether cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), or positional emission tomography (PET), have acquired a prominent place in the diagnostic process of a cognitive disorder. They are an integral part of the diagnostic criteria for Alzheimer's disease (AD) and its main differential diagnosis, frontotemporal dementia (FTD). In 2021, however, histological analysis, where pathological changes are observed directly on tissues, often remains the only method allowing a diagnosis of certainty.In 1992, the Lille Memory Resource and Research Center (CMRR) set up a network of memory consultations in the Nord Pas-de-Calais region. In addition to standardizing care, it has set up a database that now includes over 120,000 patients. Based on this large active file, our work consisted in studying the clinical and biochemical characteristics of AD and FTD patients on different scales (rare but perfectly characterized cases of clinicopathological correlations, monocentric cohorts of patients having undergone lumbar puncture, regional or international cohorts).Our first study focused on the correlations between the biochemical profile of cerebrospinal fluid (CSF) and post-mortem findings. We were able to show that amyloid and tau biomarkers are less sensitive to the corresponding pathologies when these are not yet fully developed in the cortex, leading to incomplete detection of patients with AD-related neuropathological changes.We subsequently focused on AD patients with pathological tau and pTau biomarkers in the CSF, pathological Aβ42/Aβ40 ratio, but normal Aβ42 levels. We showed that the cognitive, morphological, and functional profile of patients with AD and normal Aβ42 does not differ from those with pathological Aβ42.In the setting of FTD, CSF biomarkers are used to rule out a possible diagnosis of AD. Nevertheless, if this is the case, a whole spectrum of pathology remains possible as FTD is so heterogeneous. There are currently few established phenotype-pathology correlations, which, at the dawn of the development of a targeted treatment, may represent a loss of chance for these patients. We wished to constitute a multicentric cohort of patients with confirmed post-mortem FTD, in order to improve clinicopathological correlations. This preliminary work demonstrates the complexity of the FTD spectrum, with many phenotypic and histological overlaps.In addition to this study of gold standard FTD patients, we wished to consider the entire FTD active file of the Nord Pas-de-Calais memory consultation network. Although this disease is rare, the pooling of data within the network allowed us to reach a large number of patients. This work allowed us to demonstrate that FTD differs from AD, both in terms of initial characteristics, speed of progression and treatment. Despite the use of the latest clinical criteria, these pathologies remain under-diagnosed and should no longer be considered as limited to young subjects.Although each memory center, individually, is in a position to contribute to the advancement of science and to help better understand neurodegenerative diseases, it seems obvious at this time that the pooling of health data is indispensable. Within the framework of the European Human Brain Project, we have worked on the implementation of a federated data analysis tool. The Medical Informatics Platform allows complex analyses to be carried out from geographically distant databases, thus avoiding transfers and the risk of health data leaks between research centers.Data from routine care is abundant and contains a lot of information. It is up to us to make the most of it to advance our understanding of neurocognitive diseases, a challenge for the years to come
Ziemssen, Tjalf, and Katja Thomas. "Alemtuzumab in the long-term treatment of relapsing-remitting multiple sclerosis: an update on the clinical trial evidence and data from the real world." Sage, 2017. https://tud.qucosa.de/id/qucosa%3A35541.
Повний текст джерелаDeshotel, Matthew Wayne. "Enhancing Undergraduate Water Resources Engineering Education Using Data and Modeling Resources Situated in Real-world Ecosystems| Design Principles and Challenges for Scaling and Sustainability." Thesis, University of Louisiana at Lafayette, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10266036.
Повний текст джерелаRecent research and technological advances in the field of hydrology and water resources call for parallel educational reforms at the undergraduate level. This thesis describes the design, development, and evaluation of a series of undergraduate learning modules that engage students in investigative and inquiry-based learning experiences and introduces data analysis and numerical modeling skills. The modules are situated in the coastal hydrologic basins of Louisiana, USA. Centered on the current crisis of coastal land loss in the region, the modules immerse students in a suite of active-learning experiences in which they prepare and analyze data, reproduce model simulations, interpret results, and balance the beneficial and detrimental impacts of several real-world coastal restoration projects. The modules were developed using a web-based design that includes geospatial visualization via a built-in map-interface, textual instructions, video tutorials, and immediate feedback mechanisms. Following pilot implementations, an improvement-focused evaluation was conducted to examine the effectiveness of the modules and their potential for advancing students’ experiences with modeling-based analysis in hydrology and water resources. Both qualitative and quantitative data was collected including Likert-scale surveys, student performance grades, informal interviews, and text-response surveys. Students’ perceptions indicated that data and modeling-driven pedagogy using local real-world projects contributed to their learning and served as an effective supplement to instruction. The evaluation results also pointed out some key aspects on how to design effective and conducive undergraduate learning experiences that adopt technology-enhanced, data and modeling-based strategies, and how to pedagogically strike a balance between sufficient module complexity, ensurance of students’ continuous engagement, and flexibility to fit within existing curricula limitations. Additionally, to investigate how such learning modules can achieve large scale adoption, a total of 100 interviews were conducted with academic instructors and practicing professionals in the field of hydrology and water resources engineering. Key perspectives indicate that future efforts should appease hindering factors such as steep learning curves, lack of assessment data, refurbishment requirements, rigidness of material, time limitations.
Cenzer, Irena [Verfasser], and Helmut [Akademischer Betreuer] Ostermann. "Geriatrics principles in health care of older adults and the use of real-world data in aging-related research / Irena Cenzer ; Betreuer: Helmut Ostermann." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2020. http://d-nb.info/1221960636/34.
Повний текст джерелаGulati, Mayank. "Bridging Sim-to-Real Gap in Offline Reinforcement Learning for Antenna Tilt Control in Cellular Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-292948.
Повний текст джерелаAntennlutning är den vinkel som dämpas av strålningsstrålen och det horisontella planet. Denna vinkel spelar en viktig roll för att bestämma täckningen och störningen av nätverket med angränsande celler och intilliggande basstationer. Traditionella metoder för nätverksoptimering förlitar sig på regelbaserad heuristik för att göra beslutsfattande för antennlutningsoptimering för att uppnå önskade nätverksegenskaper. Dessa metoder är dock ganska styva och är oförmögna att fånga dynamiken i kommunikationstrafiken. De senaste framstegen inom förstärkningsinlärning har gjort det till en lönsam lösning att lösa detta problem, men även denna inlärningsmetod är antingen begränsad till dess simuleringsmiljö eller är begränsad till off-policy offline inlärning. Hittills har inga ansträngningar gjorts för att övervinna de tidigare nämnda begränsningarna för att göra det tillämpligt i den verkliga världen. Detta arbete föreslår en metod som består i att överföra förstärkningsinlärningspolicyer från en simulerad miljö till en verklig miljö, dvs. sim-till-verklig överföring genom användning av offline-lärande. Metoden använder en simulerad miljö och en fast dataset för att kompensera för de understrukna begränsningarna. Den föreslagna sim-till-verkliga överföringstekniken använder en hybridpolicymodell, som består av en del utbildad i simulering och en del utbildad på offline-verkliga data från mobilnätverk. Detta gör det möjligt att slå samman prover från verklig data till den simulerade miljön och därmed modifiera standardutbildningsförfarandena för förstärkning genom kunskapsdelning mellan de två miljöernas representationer. Å ena sidan möjliggör simulering att uppnå bättre generaliseringsprestanda med avseende på konventionellt offlineinlärning eftersom det kompletterar offlineinlärning med inlärning genom osynliga simulerade banor. Å andra sidan möjliggör offline-inlärningsförfarandet att stänga sim-till-real-klyftan genom att exponera agenten för verkliga dataprov. Följaktligen möjliggör detta överföringsinlärningsregime att upprätta optimal antennlutningskontroll som i sin tur resulterar i förbättrad täckning och minskad störning med angränsande celler i mobilnätet.
Telikapalli, Surya. "Collaborative design (COLLDESIGN): A real-time interactive unified modeling language tool." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2669.
Повний текст джерелаFerreira, E. (Eija). "Model selection in time series machine learning applications." Doctoral thesis, Oulun yliopisto, 2015. http://urn.fi/urn:isbn:9789526209012.
Повний текст джерелаTiivistelmä Mallinvalinta on oleellinen osa minkä tahansa käytännön mallinnusongelman ratkaisua. Koska mallinnettavan ilmiön toiminnan taustalla olevaa todellista mallia ei voida tietää, on mallinvalinnan tarkoituksena valita malliehdokkaiden joukosta sitä lähimpänä oleva malli. Tässä väitöskirjassa käsitellään mallinvalintaa aikasarjamuotoista dataa sisältävissä sovelluksissa neljän koneoppimisprosessissa yleisesti noudatetun askeleen kautta: aineiston esikäsittely, algoritmin valinta, piirteiden valinta ja validointi. Väitöskirjassa tutkitaan, kuinka käytettävissä olevan aineiston ominaisuudet ja määrä tulisi ottaa huomioon algoritmin valinnassa, ja kuinka aineisto tulisi jakaa mallin opetusta, testausta ja validointia varten mallin yleistettävyyden ja tulevan suorituskyvyn optimoimiseksi. Myös erityisiä rajoitteita ja vaatimuksia tavanomaisten koneoppimismenetelmien soveltamiselle aikasarjadataan käsitellään. Työn tavoitteena on erityisesti tuoda esille mallin ylioppimiseen ja ylivalintaan liittyviä ongelmia, jotka voivat seurata mallinvalin- tamenetelmien huolimattomasta tai osaamattomasta käytöstä. Työn käytännön tulokset perustuvat koneoppimismenetelmien soveltamiseen aikasar- jadatan mallinnukseen kolmella eri tutkimusalueella: pistehitsaus, fyysisen harjoittelun aikasen energiankulutuksen arviointi sekä kognitiivisen kuormituksen mallintaminen. Väitöskirja tarjoaa näihin tuloksiin pohjautuen yleisiä suuntaviivoja, joita voidaan käyttää apuna lähdettäessä ratkaisemaan uutta koneoppimisongelmaa erityisesti aineiston ominaisuuksien ja määrän, laskennallisten resurssien sekä ongelman mahdollisen aikasar- jaluonteen näkökulmasta. Työssä pohditaan myös mallin lopullisen toimintaympäristön asettamien käytännön näkökohtien ja rajoitteiden vaikutusta algoritmin valintaan
Lanera, Corrado. "Sviluppo e applicazione di tecniche di apprendimento automatico per l'analisi e la classificazione del testo in ambito clinico. Development and Application of Machine Learning Techniques for Text Analyses and Classification in Clinical Research." Doctoral thesis, Università degli studi di Padova, 2020. http://hdl.handle.net/11577/3426256.
Повний текст джерелаIl contenuto delle cartelle cliniche elettroniche (EHR) è estremamente eterogeneo, dipendendo della struttura generale del sistema sanitario. Al loro interno, il testo libero èprobabilmente la tipologia di dati non strutturato più presente e contemporaneamente sottoutilizzato. Al giorno d'oggi, grazie alle tecniche di Machine Learning (MLT), possiamo sfruttare modelli automatici per codificarne il contenuto testuale con prestazioni comparabili a quelle umane. In questa tesi, l'attenzione si concentra sull'investigazione delle MLT per l'ottenimento di informazioni utili non triviali dal testo libero in contesti clinici. Abbiamo considerato due tipi principali di testo libero coinvolti nella ricerca clinica. Il primo è composto da documenti estesi come articoli scientifici o protocolli di studio. Per questo gruppo, abbiamo preso in considerazione 14 revisioni sistematiche (SR), tra cui 7.494 studi di PubMed e un'intera istantanea composta da 233.609 studi clinici da ClinicalTrials.gov. Le cartelle cliniche elettroniche pediatriche compongono il secondo gruppo, per il quale abbiamo considerato due fonti di dati: una di 6.903.035 visite dal database italiano Pedianet e la seconda da 2.723 note di dimissione ospedaliera scritte in spagnolo e provenienti dai dipartimenti di emergenza (DE) pediatrica di nove ospedali in Nicaragua. Il primo contributo riportato è un sistema automatico addestrato per replicare una ricerca dai motori di ricerca specializzati ai registri clinici. Il modello proposto ha mostrato prestazioni di classificazione molto elevate (AUC dal 93,4% al 99,9% tra i 14 SR), con il valore aggiunto di una quantità ridotta di studi non rilevanti estratti (media di 472 e massimo di 2119 record aggiuntivi rispetto a 572 e 2680 dell'estrazione manuale originale rispettivamente). Viene riportato anche uno studio comparativo per esplorare l'effetto dell'utilizzo di differenti MLT e di metodi diversi per gestire gli effetti dello squilibro di numerosità nelle classi. Nella tesi è riportata inoltre un'intera indagine sulle visite pediatriche presso i DE raccolte presso i nove ospedali del Nicaragua. In tale indagine emerge un'accuratezza media nella classificazione delle diagnosi di dimissione coi modelli proposti del 78,31%, mostrando promettenti prestazioni per un sistema ML per la classificazione automatica delle diagnosi di dimissione da testo libero in lingua spagnola. Un ulteriore contributo riportato ha mirato a migliorare l'accuratezza del rilevamento delle malattie infettive a livello di popolazione. Questo è un problema cruciale per la salute pubblica che può fornire le informazioni di base necessarie per l'implementazione di strategie di controllo efficaci, come la notifica e il monitoraggio di efficacia di campagne di vaccinazione. Tra i due studi riportati, sono stati esplorati entrambi i paradigmi primari di ML classici e profondi. In entrambi i casi i risultati sono stati molto promettenti; nel secondo, raggiungendo prestazioni paragonabili a quelle umane (precisione del 96,59% rispetto al 95,91% raggiunta dagli annotatori umani e livello F1 bilanciato del 95,47% rispetto al 93,47%). Un ulteriore obiettivo secondario ma rilevante raggiunto riguarda le lingue indagate. La ricerca internazionale sull'uso delle MLT per classificare gli EHR si concentra principalmente su set di dati testuali in lingua inglese. Pertanto, i risultati su database non inglesi, come il Pedianet italiano o quello spagnolo delle visite ED considerate nella tesi, risultano contributi chiave per valutare l'applicabilità generale delle MLT a livello linguistico generale. Mostrando prestazioni paragonabili a quelle umane, la tesi evidenzia la reale possibilità di iniziare a incorporare i sistemi ML nella pratica clinica quotidiana per produrre un miglioramento concreto nei processi sanitari quando si tiene conto del testo libero.
Canavan, Caroline. "Using real world data to generate health economic models : a worked example assessing the cost-effectiveness of referral to gastroenterology for irritable bowel syndrome in the UK." Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/32666/.
Повний текст джерелаCars, Thomas. "Real-Time Monitoring of Healthcare Interventions in Routine Care : Effectiveness and Safety of Newly Introduced Medicines." Doctoral thesis, Uppsala universitet, Kardiovaskulär epidemiologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-304324.
Повний текст джерелаHiroi, Shinzo. "Impact of health insurance coverage for Helicobacter pylori gastritis on the trends in eradication therapy in Japan: retrospective observational study and simulation study based on real world data." Kyoto University, 2018. http://hdl.handle.net/2433/232454.
Повний текст джерела