Relevant bibliographies by topics / Biomedical Informatics

Academic literature on the topic 'Biomedical Informatics'

Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Biomedical Informatics"

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Masic, Izet. "Acta Informatica Medica Journal Review in 2021." Acta Informatica Medica 30, no. 1 (2022): 88. http://dx.doi.org/10.5455/aim.2022.30.88-90.

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Acta Informatica Medica journal (www.actainformmed.org), as Biomedical Informatics journal, during past 30 years of existing played important role in distribution of knowledge and experience within this scientific field, by publishing contributions of the biomedical experts from worlwide and spreading of Biomedical informatics knowledge and experiences in scientific and academic community. Acta Informatica Medica journal has been founded in the year 1993 as official journal of Bosnian-Herzegovinan Society of Medical Informatics (BHSMI). In the year 2019 Acta Informatica Medica has been accepted as official journal of the European Federation for Medical Informatics (www.efmi.org), besides 3 other journals: International Journal of Medical Informatics, Methods of Information in Medicine and European Journal of Biomedical Informatics. Journal Acta Informatica Medica is abstracted and indexed in 30 on-line data bases, including Pubmed, Pubmed Central, Scopus, Embase, Hinari, etc. The journal follows the Guidelines and recommendations of ICJME, COPE, EASE, WAME, etc. as well as the recommendations of the “Sarajevo Declaration on Integrity and Visibility of Scholarly Journals”, accepted by 17 Editors of biomedical journals at “SWEP 2018” Conference held in Sarajevo and printed in the countries in South-Eastern Europe. The journal supports presentations at conferences held in Bosnia and Herzegovina. The abstract papers presented at “The Mediterranean Seminar on Science Writing, Editing and Publishing“ – “SWEP 2016”, “SWEP 2018”; “SWEP 2020” and “SWEP 2021”, also found its place in the journal, by which we met our goal of promoting science and scientific publication at the area of Bosnia and Herzegovina and other countries in the region. SCImago rank for 2021 announced the bibliometric list of the journals deposited in SCOPUS indexed database. On the list are 16 journals which are published in Bosnia and Herzegovina, and between them are 7 within biomedical sciences. Three highest are Bosnian Journal of Basic Medical Sciences - H-Index is 29, Medical Archives - H-Index is 26 and Acta Informatica Medica - H-Index is 24, etc. Acta Informatica Medical journal has Impact Score, Overall Ranking, h-index, SJR, Rating, Publisher updated on May 27, 2022: Impact Score - 1.87; h-Index - 24; Rank -12749 and SJR - 0.372.
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Schleyer, T. K. "Dental Informatics: An Emerging Biomedical Informatics Discipline." Advances in Dental Research 17, no. 1 (December 2003): 4–8. http://dx.doi.org/10.1177/154407370301700103.

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Biomedical informatics is a maturing discipline. During the last forty years, it has developed into a research discipline of significant scale and scope. One of its subdisciplines, dental informatics, is beginning to emerge as its own entity. While there is a growing cadre of trained dental informaticians, dental faculty and administrators in general are not very familiar with dental informatics as an area of scientific inquiry. Many confuse informatics with information technology (IT), are unaware of its scientific methods and principles, and cannot relate dental informatics to biomedical informatics as a whole. This article delineates informatics from information technology and explains the types of scientific questions that dental and other informaticians typically explore. Scientific investigation in informatics centers primarily on model formulation, system development, system implementation, and the study of effects. Informatics draws its scientific methods mainly from information science, computer science, cognitive science, and telecommunications. Dental informatics shares many types of research questions and methods with its parent discipline, biomedical informatics. However, there are indications that certain research questions in dental informatics require novel solutions that have not yet been developed in other informatics fields.
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Ammenwerth, E., H. Dickhaus, P. Knaup, C. Lovis, J. Mantas, V. Maojo, F. J. Martin-Sanchez, et al. "Biomedical Informatics – A Confluence of Disciplines?" Methods of Information in Medicine 50, no. 06 (2011): 508–24. http://dx.doi.org/10.3414/me11-06-0003.

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SummaryBackground: Biomedical informatics is a broad discipline that borrows many methods and techniques from other disciplines.Objective: To reflect a) on the character of biomedical informatics and to determine whether it is multi-disciplinary or inter-disciplinary; b) on the question whether biomedical informatics is more than the sum of its supporting disciplines and c) on the position of biomedical informatics with respect to related disciplines.Method: Inviting an international group of experts in biomedical informatics and related disciplines on the occasion of the 50th anniversary of Methods of Information in Medicine to present their viewpoints.Results and Conclusions: This paper contains the reflections of a number of the invited experts on the character of biomedical informatics. Most of the authors agree that biomedical informatics is an interdisciplinary field of study where researchers with different scientific backgrounds alone or in combination carry out research. Biomedical informatics is a very broad scientific field and still expanding, yet comprised of a constructive aspect (designing and building systems). One author expressed that the essence of biomedical informatics, as opposed to related disciplines, lies in the modelling of the biomedical content. Interdisciplinarity also has consequences for education. Maintaining rigid disciplinary structures does not allow for sufficient adaptability to capitalize on important trends nor to leverage the influences these trends may have on biomedical informatics. It is therefore important for students to become aware of research findings in related disciplines. In this respect, it was also noted that the fact that many scientific fields use different languages and that the research findings are stored in separate bibliographic databases makes it possible that potentially connected findings will never be linked, despite the fact that these findings were published. Bridges between the sciences are needed for the success of biomedical informatics.
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Lovis, C. "Evidence-based Biomedical Informatics." Yearbook of Medical Informatics 22, no. 01 (August 2013): 47–50. http://dx.doi.org/10.1055/s-0038-1638831.

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Summary Objectives: An overview of current trends and achievements in building more evidence of using information sciences technologies in biomedical informatics. Methods: Extensive search using PubMed for published papers in this field in 2012. A selection process organized in three steps: a) identification and first selection of papers; b) international peer-review by at least 4 reviewers for each paper; c) final selection of five papers by the editorial board of the Yearbook based on the international reviewing results and a balanced coverage of the topics. Results: Synopsis of the articles selected for the IMIA Yearbook 2012 and an invited opinion paper written by leading scientists in this field. Conclusion: Evidence based health informatics is an important and ubiquitous trend in biomedical informatics. However, this research field has to be enhanced even further and, more importantly, achievements have to be put in practice.
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Johnson, L. A. "Biomedical Informatics Training for Dental Researchers." Advances in Dental Research 17, no. 1 (December 2003): 29–33. http://dx.doi.org/10.1177/154407370301700108.

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Dental researchers collaborating closely with biomedical informaticians have achieved many advances in oral health research, such as in mapping human genetics and addressing oral health disparities. Advances will continue to increase as dental researchers and biomedical informaticians study each others’ disciplines to increase the effectiveness of their collaborative research. The combined skills will greatly increase the effectiveness of dental research. This manuscript summarizes the core of biomedical informatics curriculum (biomedical informatics knowledge, data management, and software engineering) for dental research. It also summarizes the obstacles that must be overcome for all dental research students to receive the training in biomedical informatics they require. These issues are: a lack of biomedical informatics faculty, a lack of biomedical informatics courses, and a lack of accreditation standards. Last, intra- and inter-institutional collaboration solutions are described. “The decades ahead will be witness to advances in science and technology as yet unforeseen. Dentistry will benefit from these advances and must be intimately involved in their progression.” ( American Dental Association, 2002 )
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Masys, Daniel. "Biomedical Informatics." JAMA 296, no. 21 (December 6, 2006): 2620. http://dx.doi.org/10.1001/jama.296.21.2624.

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Pape, L., C. D. Page, J. W. Shavlik, G. N. Phillips, P. Brennan, and D. J. Severtson. "Biomedical Informatics Training at the University of Wisconsin-Madison." Yearbook of Medical Informatics 16, no. 01 (August 2007): 149–56. http://dx.doi.org/10.1055/s-0038-1638539.

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SummaryThe purpose of this paper is to describe biomedical informatics training at the University of Wisconsin-Madison (UW Madison).We reviewed biomedical informatics training, research, and faculty/trainee participation at UW-Madison.There are three primary approaches to training 1) The Computation & Informatics in Biology & Medicine Training Program, 2) formal biomedical informatics offered by various campus departments, and 3) individualized programs. Training at UW-Madison embodies the features of effective biomedical informatics training recommended by the American College of Medical Informatics that were delineated as: 1) curricula that integrate experiences among computational sciences and application domains, 2) individualized and interdisciplinary cross training among adiverse cadre of trainees to develop key competencies that he or she does not initially possess, 3) participation in research and development activities, and 4) exposure to a range of basic informational and computational sciences.The three biomedical informatics training approaches immerse students in multidisciplinary training and education that is supported by faculty trainers who participate in collaborative research across departments. Training is provided across a range of disciplines and available at different training stages. Biomedical informatics training at UW-Madison illustrates how a large research University, with multiple departments across biological, computational and health fields, can provide effective and productive biomedical informatics training via multiple bioinformatics training approaches.
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Wigertz, O., J. Persson, and H. Ahlfeldt. "Teaching Medical Informatics to Biomedical Engineering Students: Experiences over 15 Years." Methods of Information in Medicine 28, no. 04 (October 1989): 309–12. http://dx.doi.org/10.1055/s-0038-1636807.

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Abstract:The Departments of Biomedical Engineering and Medical Informatics at Linkoping University in Sweden were established in 1972-1973. The main purpose was to develop and offer courses in medicine, biomedical engineering and medical informatics to students in electrical engineering and computer science, for a specialization in biomedical engineering and medical informatics. The courses total about 400 hours of scheduled study in the subjects of basic cell biology, basic medicine (terminology, anatomy, physiology), biomedical engineering and medical informatics. Laboratory applications of medical computing are mainly taught in biomedical engineering courses, whereas clinical information systems, knowledge based decision support and computer science aspects are included within the medical informatics courses.
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Ammenwerth, E., and W. O. Hackl. "Job Profiles of Biomedical Informatics Graduates." Methods of Information in Medicine 54, no. 04 (2015): 372–75. http://dx.doi.org/10.3414/me14-01-0139.

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SummaryBackground: Biomedical informatics programs exist in many countries. Some analyses of the skills needed and of recommendations for curricular content for such programs have been published. However, not much is known of the job profiles and job careers of their graduates.Objectives: To analyse the job profiles and job careers of 175 graduates of the biomedical informatics bachelor and master program of the Tyrolean university UMIT.Methods: Survey of all biomedical informatics students who graduated from UMIT between 2001 and 2013.Results: Information is available for 170 graduates. Eight percent of graduates are male. Of all bachelor graduates, 86% started a master program. Of all master graduates, 36% started a PhD. The job profiles are quite diverse: at the time of the survey, 35% of all master graduates worked in the health IT industry, 24% at research institutions, 9% in hospitals, 9% as medical doctors, 17% as informaticians outside the health care sector, and 6% in other areas. Overall, 68% of the graduates are working as biomedical informaticians. The results of the survey indicate a good job situation for the graduates.Conclusions: The job opportunities for biomedical informaticians who graduated with a bachelor or master degree from UMIT seem to be quite good. The majority of graduates are working as biomedical informaticians. A larger number of comparable surveys of graduates from other biomedical informatics programs would help to enhance our knowledge about careers in biomedical informatics.
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Garcia-Remesal, M., C. Bielza, J. Crespo, D. Perez-Rey, C. Kulikowski, and V. Maojo. "Biomedical Informatics Publications: a Global Perspective." Methods of Information in Medicine 51, no. 02 (2012): 131–37. http://dx.doi.org/10.3414/me11-01-0061.

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SummaryBackground: Biomedical Informatics (BMI) is a broad discipline, having evolved from both Medical Informatics (MI) and Bioinformatics (BI). An analysis of publications in the field-should provide an indication about the geographic distribution of BMI research contributions and possible lessons for the future, both for research and professional practice.Objectives: In part I of our analysis of biomedical informatics publications we presented results from BMI conferences. In this second part, we analyse BMI journals, which provide a broader perspective and comparison between data from conferences and journals that ought to confirm or suggest alternatives to the original distributional findings from the conferences.Methods: We manually collected data about authors and their geographical origin from various MI journals: the International Journal of Medical Informatics (IJMI), the Journal of Biomedical Informatics (JBI), Methods of In-formation in Medicine (MIM) and The Journal of the American Medical Informatics Association (JAMIA). Focusing on first authors, we also compared these findings with data from the journal Bioinformatics.Results: Our results confirm those obtained in our analysis of BMI conferences – that local and regional authors favor their corresponding MI journals just as they do their conferences. Consideration of other factors, such as the increasingly open source nature of data and software tools, is consistent with these findingsConclusions: Our analysis suggests various indicators that could lead to further, deeper analyses, and could provide additional insights for future BMI research and professional activities.
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Dissertations / Theses on the topic "Biomedical Informatics"

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Moffitt, Richard Austin. "Quality control for translational biomedical informatics." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/34721.

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Translational biomedical informatics is the application of computational methods to facilitate the translation of basic biomedical science to clinical relevance. An example of this is the multi-step process in which large-scale microarray-based discovery experiments are refined into reliable clinical tests. Unfortunately, the quality of microarray data is a major issue that must be addressed before microarrays can reach their full potential as a clinical molecular profiling tool for personalized and predictive medicine. A new methodology, titled caCORRECT, has been developed to replace or augment existing microarray processing technologies, in order to improve the translation of microarray data to clinical relevance. Results of validation studies show that caCORRECT is able to improve the mean accuracy of microarray gene expression by as much as 60%, depending on the magnitude and size of artifacts on the array surface. As part of a case study to demonstrate the widespread usefulness of caCORRECT, the entire pipeline of biomarker discovery has been executed for the clinical problem of classifying Renal Cell Carcinoma (RCC) specimens into appropriate subtypes. As a result, we have discovered and validated a novel two-gene RT-PCR assay, which has the ability to diagnose between the Clear Cell and Oncocytoma RCC subtypes with near perfect accuracy. As an extension to this work, progress has been made towards a quantitative quantum dot immunohistochemical assay, which is expected to be more clinically viable than a PCR-based test.
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Stokes, Todd Hamilton. "Development of a visualization and information management platform in translational biomedical informatics." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/33967.

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Translational Biomedical Informatics (TBMI) is an emerging discipline expanding beyond traditional bioinformatics, with a focus on developing computational technologies for real-world biomedical practice. The goal of my Ph.D. research is to address a few key challenges in TBI, including: (1) the high quality and reproducibility required by medical applications when processing high throughput data, (2) the need for knowledge management solutions that allow molecular data to be handled and evaluated by researchers, regulators, and doctors collectively, (3) the need for near real-time, efficient access to decision-oriented visualizations of integrated data and data processing results, and (4) the need for an integrated solution that can evolve as medical consensus evolves, without requiring retraining, overhaul or replacement. This dissertation resulted in the development and adoption of concrete web-based application deliverables in regular use by bioinformaticians, clinicians, biologists and nanotechnologists. These include: the Chip Artifact Correction (caCORRECT) web site and grid services, the ArrayWiki community microarray repository, and the SimpleVisGrid visualization grid services (including eGOMiner, nanoDRIVE, PathwayVis and SphingoVisGrid).
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Cao, Xi Hang. "On Leveraging Representation Learning Techniques for Data Analytics in Biomedical Informatics." Diss., Temple University Libraries, 2019. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/586006.

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Computer and Information Science
Ph.D.
Representation Learning is ubiquitous in state-of-the-art machine learning workflow, including data exploration/visualization, data preprocessing, data model learning, and model interpretations. However, the majority of the newly proposed Representation Learning methods are more suitable for problems with a large amount of data. Applying these methods to problems with a limited amount of data may lead to unsatisfactory performance. Therefore, there is a need for developing Representation Learning methods which are tailored for problems with ``small data", such as, clinical and biomedical data analytics. In this dissertation, we describe our studies of tackling the challenging clinical and biomedical data analytics problem from four perspectives: data preprocessing, temporal data representation learning, output representation learning, and joint input-output representation learning. Data scaling is an important component in data preprocessing. The objective in data scaling is to scale/transform the raw features into reasonable ranges such that each feature of an instance will be equally exploited by the machine learning model. For example, in a credit flaw detection task, a machine learning model may utilize a person's credit score and annual income as features, but because the ranges of these two features are different, a machine learning model may consider one more heavily than another. In this dissertation, I thoroughly introduce the problem in data scaling and describe an approach for data scaling which can intrinsically handle the outlier problem and lead to better model prediction performance. Learning new representations for data in the unstandardized form is a common task in data analytics and data science applications. Usually, data come in a tubular form, namely, the data is represented by a table in which each row is a feature (row) vector of an instance. However, it is also common that the data are not in this form; for example, texts, images, and video/audio records. In this dissertation, I describe the challenge of analyzing imperfect multivariate time series data in healthcare and biomedical research and show that the proposed method can learn a powerful representation to encounter various imperfections and lead to an improvement of prediction performance. Learning output representations is a new aspect of Representation Learning, and its applications have shown promising results in complex tasks, including computer vision and recommendation systems. The main objective of an output representation algorithm is to explore the relationship among the target variables, such that a prediction model can efficiently exploit the similarities and potentially improve prediction performance. In this dissertation, I describe a learning framework which incorporates output representation learning to time-to-event estimation. Particularly, the approach learns the model parameters and time vectors simultaneously. Experimental results do not only show the effectiveness of this approach but also show the interpretability of this approach from the visualizations of the time vectors in 2-D space. Learning the input (feature) representation, output representation, and predictive modeling are closely related to each other. Therefore, it is a very natural extension of the state-of-the-art by considering them together in a joint framework. In this dissertation, I describe a large-margin ranking-based learning framework for time-to-event estimation with joint input embedding learning, output embedding learning, and model parameter learning. In the framework, I cast the functional learning problem to a kernel learning problem, and by adopting the theories in Multiple Kernel Learning, I propose an efficient optimization algorithm. Empirical results also show its effectiveness on several benchmark datasets.
Temple University--Theses
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Koay, Pei P. "(Re)presenting Human Population Database Projects: virtually designing and siting biomedical informatics ventures." Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/27709.

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This dissertation examines the politics of representation in biotechnosciences. Through web representations, I examine three emerging endeavors that propose to create large-scale human population genomic databases to study complex, common diseases and conditions. These projects were initiated in different nations (US, UK, and Iceland), created under different institutional configurations, and are at various stages of development. The websites, which are media technologies do not simply reflect and promote these endeavors. Rather, they help shape these database projects in which the science is uncertain and the technologies not yet built. Thus, they are constitutive technologies that affect the construction of these database projects. More needs to be done to explore how to interpret the 'virtual' realm and how it relates to the 'real' world and specific situations. By bringing hypertextuality into the analysis, I explore how knowledges, practices, and subjectivities are created. By adapting the methods of a number of science and technology (STS) authors, I develop a more dynamic lens in which to investigate web representations and 'emerging' biomedical projects. My concern however, is not only in what represents what, but how representations are constructed. The power of the latter derives from its invisibility. In re-conceptualizing representation and new media technologies, I show that these sites are techno-social spaces for creating knowledge, specific ways of seeing, and practicing biomedicine today. The narrowing time/space between generating data, releasing information, and incorporating publics into their endeavors raises crucial issues as to how biomedicine is represented and how broader audiences are engaged. In the dominant discourses, these projects are all situated within biomedical, (post)genomic, and information revolutions. Here, they hang on the technological object, the database, with the ability to contain what we are coming to understand as life/genetic/bio information. Through the moves of both treating these databases as part of a complex system and investigating them through a lens of representation, I begin to include potential participants and broader audiences into the analysis. Informatic bodies, populations, and subjects are co-created at, by, and through these sites as the developing database projects and information are (re)presented.
Ph. D.
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Samuel, Jarvie John. "Elicitation of Protein-Protein Interactions from Biomedical Literature Using Association Rule Discovery." Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc30508/.

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Extracting information from a stack of data is a tedious task and the scenario is no different in proteomics. Volumes of research papers are published about study of various proteins in several species, their interactions with other proteins and identification of protein(s) as possible biomarker in causing diseases. It is a challenging task for biologists to keep track of these developments manually by reading through the literatures. Several tools have been developed by computer linguists to assist identification, extraction and hypotheses generation of proteins and protein-protein interactions from biomedical publications and protein databases. However, they are confronted with the challenges of term variation, term ambiguity, access only to abstracts and inconsistencies in time-consuming manual curation of protein and protein-protein interaction repositories. This work attempts to attenuate the challenges by extracting protein-protein interactions in humans and elicit possible interactions using associative rule mining on full text, abstracts and captions from figures available from publicly available biomedical literature databases. Two such databases are used in our study: Directory of Open Access Journals (DOAJ) and PubMed Central (PMC). A corpus is built using articles based on search terms. A dataset of more than 38,000 protein-protein interactions from the Human Protein Reference Database (HPRD) is cross-referenced to validate discovered interactive pairs. A set of an optimal size of possible binary protein-protein interactions is generated to be made available for clinician or biological validation. A significant change in the number of new associations was found by altering the thresholds for support and confidence metrics. This study narrows down the limitations for biologists in keeping pace with discovery of protein-protein interactions via manually reading the literature and their needs to validate each and every possible interaction.
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Radovanovic, Aleksandar. "Concept Based Knowledge Discovery from Biomedical Literature." Thesis, Online access, 2009. http://etd.uwc.ac.za/usrfiles/modules/etd/docs/etd_gen8Srv25Nme4_9861_1272229462.pdf.

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Milosevic, Nikola. "A multi-layered approach to information extraction from tables in biomedical documents." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/a-multilayered-approach-to-information-extraction-from-tables-in-biomedical-documents(c2edce9c-ae7f-48fa-81c2-14d4bb87423e).html.

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The quantity of literature in the biomedical domain is growing exponentially. It is becoming impossible for researchers to cope with this ever-increasing amount of information. Text mining provides methods that can improve access to information of interest through information retrieval, information extraction and question answering. However, most of these systems focus on information presented in main body of text while ignoring other parts of the document such as tables and figures. Tables present a potentially important component of research presentation, as authors often include more detailed information in tables than in textual sections of a document. Tables allow presentation of large amounts of information in relatively limited space, due to their structural flexibility and ability to present multi-dimensional information. Table processing encapsulates specific challenges that table mining systems need to take into account. Challenges include a variety of visual and semantic structures in tables, variety of information presentation formats, and dense content in table cells. The work presented in this thesis examines a multi-layered approach to information extraction from tables in biomedical documents. In this thesis we propose a representation model of tables and a method for table structure disentangling and information extraction. The model describes table structures and how they are read. We propose a method for information extraction that consists of: (1) table detection, (2) functional analysis, (3) structural analysis, (4) semantic tagging, (5) pragmatic analysis, (6) cell selection and (7) syntactic processing and extraction. In order to validate our approach, show its potential and identify remaining challenges, we applied our methodology to two case studies. The aim of the first case study was to extract baseline characteristics of clinical trials (number of patients, age, gender distribution, etc.) from tables. The second case study explored how the methodology can be applied to relationship extraction, examining extraction of drug-drug interactions. Our method performed functional analysis with a precision score of 0.9425, recall score of 0.9428 and F1-score of 0.9426. Relationships between cells were recognized with a precision of 0.9238, recall of 0.9744 and F1-score of 0.9484. The information extraction methodology performance is the state-of-the-art in table information extraction recording an F1-score range of 0.82-0.93 for demographic data, adverse event and drug-drug interaction extraction, depending on the complexity of the task and available semantic resources. Presented methodology demonstrated that information can be efficiently extracted from tables in biomedical literature. Information extraction from tables can be important for enhancing data curation, information retrieval, question answering and decision support systems with additional information from tables that cannot be found in the other parts of the document.
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Raje, Satyajeet. "ResearchIQ: An End-To-End Semantic Knowledge Platform For Resource Discovery in Biomedical Research." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354657305.

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Templeton, James Robert. "Trust and Trustworthiness: A Framework for Successful Design of Telemedicine." NSUWorks, 2010. http://nsuworks.nova.edu/gscis_etd/321.

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Trust and its antecedents have been demonstrated as a barrier to the successful adoption of numerous fields of technology, most notably e-commerce, and may be a key factor in the lack of adoption or adaptation in the field of telemedicine. In the medical arena, trust is often formed through the relationships cultivated over time via clinician and patient. Trust and interpersonal relationships may also play a significant role in the adoption of telemedicine. The idea of telemedicine has been explored for nearly 30 years in one form or another. Yet, despite grandiose promises of how it will someday significantly improve the healthcare system, the field continues to lag behind other areas of technology by 10 to 15 years. The reasons for the lack of adoption may be many given the barriers that have been observed by other researchers with regards to trust and trustworthiness. This study examined the role of trust from various aspects within telemedicine, with particular emphasis on the role that trust plays in the adoption and adaptation of a telemedicine system. Simulators examined the role of trust in the treatment and management of diabetes mellitus (common illness) in order to assess the impact and role of trust components. Surveys of the subjects were conducted to capture the trust dynamics, as well as the development of a framework for successful implementation of telemedicine using trust and trustworthiness as a foundation. Results indicated that certain attributes do influence the level of trust in the system. The framework developed demonstrated that medical content, disease state management, perceived patient outcomes, and design all had significant impact on trust of the system.
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Adejare, Adeboye A. Jr. "Equiformatics: Informatics Methods and Tools to Investigate and Address Health Disparities and Inequities." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1623164833455566.

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Books on the topic "Biomedical Informatics"

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Biomedical informatics. New York, NY: Humana Press, 2009.

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Shortliffe, Edward H., and James J. Cimino, eds. Biomedical Informatics. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58721-5.

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Astakhov, Vadim, ed. Biomedical Informatics. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-524-4.

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Holzinger, Andreas. Biomedical Informatics. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04528-3.

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Shortliffe, Edward H., and James J. Cimino, eds. Biomedical Informatics. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-4474-8.

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Shortliffe, Edward H., and James J. Cimino, eds. Biomedical Informatics. New York, NY: Springer New York, 2006. http://dx.doi.org/10.1007/0-387-36278-9.

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Hutton, John J., ed. Pediatric Biomedical Informatics. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-5149-1.

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Hutton, John J., ed. Pediatric Biomedical Informatics. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1104-7.

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Shen, Bairong, Haixu Tang, and Xiaoqian Jiang, eds. Translational Biomedical Informatics. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1503-8.

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Principles of biomedical informatics. Amsterdam: Academic Press, 2008.

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Book chapters on the topic "Biomedical Informatics"

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Munro, Paul, Hannu Toivonen, Geoffrey I. Webb, Wray Buntine, Peter Orbanz, Yee Whye Teh, Pascal Poupart, et al. "Biomedical Informatics." In Encyclopedia of Machine Learning, 132. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_81.

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Page, C. David, and Sriraam Natarajan. "Biomedical Informatics." In Encyclopedia of Machine Learning and Data Mining, 1–24. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-1-4899-7502-7_30-1.

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Page, C. David, and Sriraam Natarajan. "Biomedical Informatics." In Encyclopedia of Machine Learning and Data Mining, 143–63. Boston, MA: Springer US, 2017. http://dx.doi.org/10.1007/978-1-4899-7687-1_30.

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Rubin, Daniel L., Hayit Greenspan, and James F. Brinkley. "Biomedical Imaging Informatics." In Biomedical Informatics, 285–327. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4474-8_9.

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Rubin, Daniel L., Hayit Greenspan, and Assaf Hoogi. "Biomedical Imaging Informatics." In Biomedical Informatics, 299–362. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58721-5_10.

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Patel, Vimla L., and David R. Kaufman. "Cognitive Informatics." In Biomedical Informatics, 121–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58721-5_4.

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Tsafnat, Guy, Frank Lin, and Miew Keen Choong. "Translational Biomedical Informatics." In Encyclopedia of Systems Biology, 2275–78. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_252.

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LaVenture, Martin, David A. Ross, and William A. Yasnoff. "Public Health Informatics." In Biomedical Informatics, 503–16. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4474-8_16.

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Payne, Philip R. O., Peter J. Embi, and James J. Cimino. "Clinical Research Informatics." In Biomedical Informatics, 755–77. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4474-8_26.

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Cronin, Robert M., Holly Jimison, and Kevin B. Johnson. "Personal Health Informatics." In Biomedical Informatics, 363–89. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-58721-5_11.

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Conference papers on the topic "Biomedical Informatics"

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Athey, Brian D. "Integrative Biomedical Informatics." In 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering. IEEE, 2007. http://dx.doi.org/10.1109/bibe.2007.4375769.

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Taneja, Sanya, Richard Boyce, William Reynolds, and Denis Newman-Griffis. "Introducing Information Retrieval for Biomedical Informatics Students." In Proceedings of the Fifth Workshop on Teaching NLP. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.teachingnlp-1.16.

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"Biomedical image processing and informatics." In 2011 24th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2011. http://dx.doi.org/10.1109/cbms.2011.5999135.

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Lopez-Campos, Guillermo, Riccardo Bellazzi, and Fernando Martin-Sanchez. "Exposome, Health and Biomedical Informatics - An Emerging Discipline and Its Interaction with Current Biomedical Informatics." In International Conference on Health Informatics. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005278405800584.

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Wagholikar, A. "Career development initiatives in biomedical health informatics." In 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6347373.

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Chung, Ping-Tsai, and Hsin–Hua Hsiao. "Probabilistic Relational Database Applications for Biomedical Informatics." In 22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008). IEEE, 2008. http://dx.doi.org/10.1109/waina.2008.280.

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McGregor, Carolyn, and Monique Frize. "Women in Biomedical Engineering and Health Informatics." In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2007. http://dx.doi.org/10.1109/iembs.2007.4352267.

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McGregor, Carolyn, and Monique Frize. "Women in Biomedical Engineering and Health Informatics." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4650567.

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Eom, Tae Joong. "Real time optical imaging for biomedical informatics." In Asia-Pacific Optical Sensors Conference. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/apos.2016.w1a.1.

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Tsiknakis, Manolis. "The European cancer informatics landscape: Challenges for the biomedical informatics community." In 2008 8th IEEE International Conference on Bioinformatics and BioEngineering (BIBE). IEEE, 2008. http://dx.doi.org/10.1109/bibe.2008.4696649.

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Reports on the topic "Biomedical Informatics"

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Shriver, Craig D. Advanced Processing for Biomedical Informatics (APBI). Fort Belvoir, VA: Defense Technical Information Center, October 2007. http://dx.doi.org/10.21236/ada548832.

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Goldstein, Neal. Epidemiology Blog of Neal D. Goldstein, PhD, MBI. Neal D. Goldstein, 2023. http://dx.doi.org/10.17918/goldsteinepi.

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Musings on topics related to epidemiology, epidemiological methods, public and clinical health. Written by Neal D. Goldstein, PhD, MBI. Dr. Goldstein is an Associate Professor of Epidemiology at the Drexel University Dornsife School of Public Health. With a background in biomedical informatics, he focuses on computational approaches in complex data settings, especially electronic health records and disease surveillance, to understand infectious disease transmission. This has been demonstrated through his work with blood borne pathogens (HIV and hepatitis C), COVID-19, vaccine preventable diseases, and healthcare associated infections.
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Walker, Philip. Library Impact Practice Brief: Assessing Library Information Services and Demonstrating Value through the Tailored Design Method. Association of Research Libraries, November 2022. http://dx.doi.org/10.29242/report.vanderbilt2022.

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Demonstrating the value of a biomedical library can be a daunting and somewhat ineffective task. The current literature base contains many articles attempting to achieve this goal by analyzing the collections through resource usage and citation analysis. However, with competing budgets across university campuses, it has become essential to investigate and develop methods in which libraries can correlate collections and services as it relates to their role as a partner across the scholarly, education, and service missions of our institutions. This practice brief discusses various methods and strategies in which the Annette and Irwin Eskind Family Biomedical Library and Learning Center sought to identify, compile, analyze, and disseminate relevant data to demonstrate its impact or added value to the research enterprise at Vanderbilt University and Vanderbilt University Medical Center. This work was done as part of the library’s participation in the ARL Research Library Impact Framework initiative.
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Shi, Yue, Liqun Wu, Zehuan Liao, and Ningning Zhang. The Comparision of Impact of Chinese Medicine and Diane-35 on Sex Hormone Level in Adolescent with Polycystic Ovary Syndrome. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0031.

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Review question / Objective: The Comparision of Impact of Chinese Medicine and Diane-35 on Sex Hormone Level in Adolescent with Polycystic Ovary Syndrome. Condition being studied: Adolescent patients who met the diagnostic criteria of PCOS. Information sources: English databases (PubMed, Embase, Web of Science, and the Cochrane Library) and Chinese databases (China National Knowledge Infrastructure(CNKI), Wanfang, the China Science and Technology Journal Database (VIP), and the Chinese Biomedical Literature Database (CBM)).
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Yu, Wenyan, Xuhao Li, Yunliang Zhang, and Jiguo Yang. Effecacy and Safty of Moxibustion for Depression and Anxiety in COVID-19: A protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, May 2022. http://dx.doi.org/10.37766/inplasy2022.5.0162.

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Review question / Objective: The research aims to observe the effecacy and safty of moxibustion for anxiety and depression in COVID-19. Condition being studied: Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease that makes breathing difficult and is often accompanied by anxiety and depression. Moxibustion, a special external treatment of traditional Chinese medicine, has shown beneficial effects in the treatment of anxiety and depression. Information sources: The Cochrane Central of Controlled Trials (CENTRAL), PubMed, Embase, Chinese Biomedical Literature Database, CNKI, Weipu Chinese Science and Technology Journal Database, Wanfang Database, and related journals.
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Sun, Chenbing, Zhe Wang, and Yuening Dai. Music therapy for sleep quality in cancer patients with insomnia：A protocol for systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2021. http://dx.doi.org/10.37766/inplasy2021.12.0128.

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Review question / Objective: The aim of this systematic review is to compare music therapy in terms of efficacy in cancer patients with insomnia disorders to better inform clinical practice. Condition being studied: The effectiveness of music therapy for cancer- associate insomnia is the main interest of this systematic review. Information sources: MEDLINE (PubMed, Ovid) The Cochrane Library, Web of Science, Embase and Electronic retrieval of Chinese Biomedical Literature Database (CBM), China National Knowledge Infrastructure (CHKD-CNKI), VIP database, Wanfang Database will be searched from inception time to date. In addition, the included literature will be reviewed and relevant literature will be supplemented.
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Zeng, Siyao, Lei Ma, Lishan Yang, Xiaodong Hu, Xinxin Guo, Yi Li, Yao Zhang, et al. Advantages of damage control surgery over conventional surgery inmultiple trauma: a meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2022. http://dx.doi.org/10.37766/inplasy2022.10.0006.

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Review question / Objective: This meta-analysis aims to explore whether damage control surgery has advantages over traditional surgery in the treatment of multiple trauma. Information sources: The Chinese Biomedical literature (CBM), Chinese National Knowledge Infrastructure (CNKI), Weipu (VIP), Duxiu, WanFang, Web of sciense, PubMed, Scopus, Ovid, EMbase, ProQuest, Cochrane, Chinese clinical trial Registry and Clinical Trials.gov databases. Main outcome(s): mortality rate, the success rate of rescue, In-hospital length of stay, ICU length of stay, the overall incidence rate of complications, incidence of disseminated intravascular coagulation (DIC), incidence of multiple organ dysfunction syndrome (MODS) , incidence of shock.
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Hernández-López, Luis Pablo, Miriam Romero-López, and Guillermo García-Quirante. Humor and social competence in High School and University education: a systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2021. http://dx.doi.org/10.37766/inplasy2021.11.0033.

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Review question / Objective: Research question: What type of relationship exists between the use of humor and social competence, or any of their respective components, in post-compulsory education students? The aim of this paper was to conduct a systematic theoretical review of the relationship between humor and social competence in post-compulsory education students. Information sources: Electronic bibliographic databases of Psychology, Biomedical and Multidisciplinary Sciences, as well as the ProQuest search platform and the SCOPUS and Web of Science meta-search engines. The electronic databases used were MEDLINE, ProQuest Dissertations & Theses Global, Psychology Database, APA PsycArticles, APA PsycInfo, SCOPUS and Web of Science Core Collection. Platforms: ProQuest and the meta-search engines SCOPUS and Web of Science.
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Wei, Yuehui, Hui Mao, Ziyun Jiang, Luyao Liu, Yuqiao Quan, and Xun Li. Efficacy and safety of Zuogui Wan combined with conventional Western medicine for postmenopausal osteoporosis: A protocol for a systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2022. http://dx.doi.org/10.37766/inplasy2022.4.0099.

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Review question / Objective: The proposed systematic review of randomized controlled trials (RCTs) will address the effectiveness and safety of Zuogui Wan combined with conventional Western medicine (CWM) for osteoporosis in postmenopausal women, and provide reference for clinical practice. Information sources: We will use computers to search PubMed, Cochrane Library, Embase, Web of Science, Chinese National Knowledge Infrastructure database (CNKI), WanFang database, Chinese Biomedical Database (CMB), Chinese Science and Technology Periodical database (VIP), China Master’s Theses Full-text Database (CMFD), China Proceedings of Conference Full-text Database (CPFD), WHO International Clinical Trials Registry Platform (ICTRP), Chinese Clinical Trials Registry (ChiCTR) and ClinicalTrials.gov, and select all eligible RCTs from inception to October, 2021. Clinicians will also be consulted for additional studies.
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Guo, Jing, Yu han Chen, Chun xiao Li, Xiao Ling, Panpan Wang, Yuqing Yang, and Yingying Zhang. Meta-analysis of Kangai injection combined with radiotherapy and chemotherapy in the treatment of gynecological malignant tumors. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, June 2022. http://dx.doi.org/10.37766/inplasy2022.6.0063.

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Review question / Objective: This study systematically evaluated the clinical efficacy and safety of Kangai injection combined with radiotherapy and chemotherapy in the treatment of gynecological malignant tumors. The subjects of the study were patients with clinical diagnosis of ovarian cancer, cervical cancer, and endometrial cancer. The experimental group was given Kang'ai injection combined with radiotherapy and chemotherapy, while the control group was given conventional chemotherapy. The primary outcome was the overall clinical response rate. Secondary outcomes included quality of life, body mass, indicators of immune function, and adverse events. Information sources: Eight databases including CNKI, Wan fang Database, VIP Chinese Database, China Biomedical Literature Service System, EI, Springer, PubMed, The Cochrane Library were searched before May 2022.
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