Creating a pipeline of talent for informatics: STEM initiative for high school students in computer science, biology, and biomedical informatics.

PubMed

Dutta-Moscato, Joyeeta; Gopalakrishnan, Vanathi; Lotze, Michael T; Becich, Michael J

2014-01-01

This editorial provides insights into how informatics can attract highly trained students by involving them in science, technology, engineering, and math (STEM) training at the high school level and continuing to provide mentorship and research opportunities through the formative years of their education. Our central premise is that the trajectory necessary to be expert in the emergent fields in front of them requires acceleration at an early time point. Both pathology (and biomedical) informatics are new disciplines which would benefit from involvement by students at an early stage of their education. In 2009, Michael T Lotze MD, Kirsten Livesey (then a medical student, now a medical resident at University of Pittsburgh Medical Center (UPMC)), Richard Hersheberger, PhD (Currently, Dean at Roswell Park), and Megan Seippel, MS (the administrator) launched the University of Pittsburgh Cancer Institute (UPCI) Summer Academy to bring high school students for an 8 week summer academy focused on Cancer Biology. Initially, pathology and biomedical informatics were involved only in the classroom component of the UPCI Summer Academy. In 2011, due to popular interest, an informatics track called Computer Science, Biology and Biomedical Informatics (CoSBBI) was launched. CoSBBI currently acts as a feeder program for the undergraduate degree program in bioinformatics at the University of Pittsburgh, which is a joint degree offered by the Departments of Biology and Computer Science. We believe training in bioinformatics is the best foundation for students interested in future careers in pathology informatics or biomedical informatics. We describe our approach to the recruitment, training and research mentoring of high school students to create a pipeline of exceptionally well-trained applicants for both the disciplines of pathology informatics and biomedical informatics. We emphasize here how mentoring of high school students in pathology informatics and biomedical informatics will be critical to assuring their success as leaders in the era of big data and personalized medicine.

Job Profiles of Biomedical Informatics Graduates. Results of a Graduate Survey.

PubMed

Ammenwerth, E; Hackl, W O

2015-01-01

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. To analyse the job profiles and job careers of 175 graduates of the biomedical informatics bachelor and master program of the Tyrolean university UMIT. Survey of all biomedical informatics students who graduated from UMIT between 2001 and 2013. 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. 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.

Military research needs in biomedical informatics.

PubMed

Reifman, Jaques; Gilbert, Gary R; Fagan, Lawrence; Satava, Richard

2002-01-01

The 2001 U.S. Army Medical Research and Materiel Command (USAMRMC) Biomedical Informatics Roadmap Meeting was devoted to developing a strategic plan in four focus areas: Hospital and Clinical Informatics, E-Health, Combat Health Informatics, and Bioinformatics and Biomedical Computation. The driving force of this Roadmap Meeting was the recent accelerated pace of change in biomedical informatics in which emerging technologies have the potential to affect significantly the Army research portfolio and investment strategy in these focus areas. The meeting was structured so that the first two days were devoted to presentations from experts in the field, including representatives from the three services, other government agencies, academia, and the private sector, and the morning of the last day was devoted to capturing specific biomedical informatics research needs in the four focus areas. This white paper summarizes the key findings and recommendations and should be a powerful tool for the crafting of future requests for proposals to help align USAMRMC new strategic research investments with new developments and emerging technologies.

Building and evaluating an informatics tool to facilitate analysis of a biomedical literature search service in an academic medical center library.

PubMed

Hinton, Elizabeth G; Oelschlegel, Sandra; Vaughn, Cynthia J; Lindsay, J Michael; Hurst, Sachiko M; Earl, Martha

2013-01-01

This study utilizes an informatics tool to analyze a robust literature search service in an academic medical center library. Structured interviews with librarians were conducted focusing on the benefits of such a tool, expectations for performance, and visual layout preferences. The resulting application utilizes Microsoft SQL Server and .Net Framework 3.5 technologies, allowing for the use of a web interface. Customer tables and MeSH terms are included. The National Library of Medicine MeSH database and entry terms for each heading are incorporated, resulting in functionality similar to searching the MeSH database through PubMed. Data reports will facilitate analysis of the search service.

Biomedical informatics and the convergence of Nano-Bio-Info-Cogno (NBIC) technologies.

PubMed

Martin-Sanchez, F; Maojo, V

2009-01-01

To analyze the role that biomedical informatics could play in the application of the NBIC Converging Technologies in the medical field and raise awareness of these new areas throughout the Biomedical Informatics community. Review of the literature and analysis of the reference documents in this domain from the biomedical informatics perspective. Detailing existing developments showing that partial convergence of technologies have already yielded relevant results in biomedicine (such as bioinformatics or biochips). Input from current projects in which the authors are involved is also used. Information processing is a key issue in enabling the convergence of NBIC technologies. Researchers in biomedical informatics are in a privileged position to participate and actively develop this new scientific direction. The experience of biomedical informaticians in five decades of research in the medical area and their involvement in the completion of the Human and other genome projects will help them participate in a similar role for the development of applications of converging technologies -particularly in nanomedicine. The proposed convergence will bring bridges between traditional disciplines. Particular attention should be placed on the ethical, legal, and social issues raised by the NBIC convergence. These technologies provide new directions for research and education in Biomedical Informatics placing a greater emphasis in multidisciplinary approaches.

NASA Biomedical Informatics Capabilities and Needs

NASA Technical Reports Server (NTRS)

Johnson-Throop, Kathy A.

2009-01-01

To improve on-orbit clinical capabilities by developing and providing operational support for intelligent, robust, reliable, and secure, enterprise-wide and comprehensive health care and biomedical informatics systems with increasing levels of autonomy, for use on Earth, low Earth orbit & exploration class missions. Biomedical Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision-making process, at the time and place that a decision needs to be made.

The life and death of URLs in five biomedical informatics journals.

PubMed

Carnevale, Randy J; Aronsky, Dominik

2007-04-01

To determine the decay rate of Uniform Record Locators (URLs) in the reference section of biomedical informatics journals. URL references were collected from printed journal articles of the first and middle issues of 1999-2004 and electronically available in-press articles in January 2005. We limited this set to five biomedical informatics journals: Artificial Intelligence in Medicine, International Journal of Medical Informatics, Journal of the American Medical Informatics Association: JAMIA, Methods of Information in Medicine, and Journal of Biomedical Informatics. During a 1-month period, URL access attempts were performed eight times a day at regular intervals. Of the 19,108 references extracted from 606 printed and 86 in-press articles, 1112 (5.8%) references contained a URL. Of the 1049 unique URLs, 726 (69.2%) were alive, 230 (21.9%) were dead, and 93 (8.9%) were comatose. URLs from in-press articles included 212 URLs, of which 169 (79.7%) were alive, 21 (9.9%) were dead, and 22 (10.4%) were comatose. The average annual decay, or link rot, rate was 5.4%. The URL decay rate in biomedical informatics journals is high. A commonly accepted strategy for the permanent archival of digital information referenced in scholarly publications is urgently needed.

Ontology-Oriented Programming for Biomedical Informatics.

PubMed

Lamy, Jean-Baptiste

2016-01-01

Ontologies are now widely used in the biomedical domain. However, it is difficult to manipulate ontologies in a computer program and, consequently, it is not easy to integrate ontologies with databases or websites. Two main approaches have been proposed for accessing ontologies in a computer program: traditional API (Application Programming Interface) and ontology-oriented programming, either static or dynamic. In this paper, we will review these approaches and discuss their appropriateness for biomedical ontologies. We will also present an experience feedback about the integration of an ontology in a computer software during the VIIIP research project. Finally, we will present OwlReady, the solution we developed.

How can we improve Science, Technology, Engineering, and Math education to encourage careers in Biomedical and Pathology Informatics?

PubMed

Uppal, Rahul; Mandava, Gunasheil; Romagnoli, Katrina M; King, Andrew J; Draper, Amie J; Handen, Adam L; Fisher, Arielle M; Becich, Michael J; Dutta-Moscato, Joyeeta

2016-01-01

The Computer Science, Biology, and Biomedical Informatics (CoSBBI) program was initiated in 2011 to expose the critical role of informatics in biomedicine to talented high school students.[1] By involving them in Science, Technology, Engineering, and Math (STEM) training at the high school level and providing mentorship and research opportunities throughout the formative years of their education, CoSBBI creates a research infrastructure designed to develop young informaticians. Our central premise is that the trajectory necessary to be an expert in the emerging fields of biomedical informatics and pathology informatics requires accelerated learning at an early age.In our 4(th) year of CoSBBI as a part of the University of Pittsburgh Cancer Institute (UPCI) Academy (http://www.upci.upmc.edu/summeracademy/), and our 2nd year of CoSBBI as an independent informatics-based academy, we enhanced our classroom curriculum, added hands-on computer science instruction, and expanded research projects to include clinical informatics. We also conducted a qualitative evaluation of the program to identify areas that need improvement in order to achieve our goal of creating a pipeline of exceptionally well-trained applicants for both the disciplines of pathology informatics and biomedical informatics in the era of big data and personalized medicine.

Integration and Beyond

PubMed Central

Stead, William W.; Miller, Randolph A.; Musen, Mark A.; Hersh, William R.

2000-01-01

The vision of integrating information—from a variety of sources, into the way people work, to improve decisions and process—is one of the cornerstones of biomedical informatics. Thoughts on how this vision might be realized have evolved as improvements in information and communication technologies, together with discoveries in biomedical informatics, and have changed the art of the possible. This review identified three distinct generations of “integration” projects. First-generation projects create a database and use it for multiple purposes. Second-generation projects integrate by bringing information from various sources together through enterprise information architecture. Third-generation projects inter-relate disparate but accessible information sources to provide the appearance of integration. The review suggests that the ideas developed in the earlier generations have not been supplanted by ideas from subsequent generations. Instead, the ideas represent a continuum of progress along the three dimensions of workflow, structure, and extraction. PMID:10730596

On Contributing to the Progress of Medical Informatics as Publisher.

PubMed

Haux, R; Geissbuhler, A; Holmes, J; Jaulent, M-C; Koch, S; Kulikowski, C A; Lehmann, C U; McCray, A T; Séroussi, B; Soualmia, L F; van Bemmel, J H

2017-08-01

May 1st, 2017, will mark Dieter Bergemann's 80th birthday. As Chief Executive Officer and Owner of Schattauer Publishers from 1983 to 2016, the biomedical and health informatics community owes him a great debt of gratitude. The past and present editors of Methods of Information in Medicine, the IMIA Yearbook of Medical Informatics, and Applied Clinical Informatics want to honour and thank Dieter Bergemann by providing a brief biography that emphasizes his contributions, by reviewing his critical role as an exceptionally supportive publisher for Schattauer's three biomedical and health informatics periodicals, and by sharing some personal anecdotes. Over the past 40 years, Dieter Bergemann has been an influential, if behind-the-scenes, driving force in biomedical and health informatics publications, helping to ensure success in the dissemination of our field's research and practice. Georg Thieme Verlag KG Stuttgart.

A National Virtual Specimen Database for Early Cancer Detection

NASA Technical Reports Server (NTRS)

Crichton, Daniel; Kincaid, Heather; Kelly, Sean; Thornquist, Mark; Johnsey, Donald; Winget, Marcy

2003-01-01

Access to biospecimens is essential for enabling cancer biomarker discovery. The National Cancer Institute's (NCI) Early Detection Research Network (EDRN) comprises and integrates a large number of laboratories into a network in order to establish a collaborative scientific environment to discover and validate disease markers. The diversity of both the institutions and the collaborative focus has created the need for establishing cross-disciplinary teams focused on integrating expertise in biomedical research, computational and biostatistics, and computer science. Given the collaborative design of the network, the EDRN needed an informatics infrastructure. The Fred Hutchinson Cancer Research Center, the National Cancer Institute,and NASA's Jet Propulsion Laboratory (JPL) teamed up to build an informatics infrastructure creating a collaborative, science-driven research environment despite the geographic and morphology differences of the information systems that existed within the diverse network. EDRN investigators identified the need to share biospecimen data captured across the country managed in disparate databases. As a result, the informatics team initiated an effort to create a virtual tissue database whereby scientists could search and locate details about specimens located at collaborating laboratories. Each database, however, was locally implemented and integrated into collection processes and methods unique to each institution. This meant that efforts to integrate databases needed to be done in a manner that did not require redesign or re-implementation of existing system

The Function Biomedical Informatics Research Network Data Repository

PubMed Central

Keator, David B.; van Erp, Theo G.M.; Turner, Jessica A.; Glover, Gary H.; Mueller, Bryon A.; Liu, Thomas T.; Voyvodic, James T.; Rasmussen, Jerod; Calhoun, Vince D.; Lee, Hyo Jong; Toga, Arthur W.; McEwen, Sarah; Ford, Judith M.; Mathalon, Daniel H.; Diaz, Michele; O’Leary, Daniel S.; Bockholt, H. Jeremy; Gadde, Syam; Preda, Adrian; Wible, Cynthia G.; Stern, Hal S.; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G.

2015-01-01

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical datasets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 dataset consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 Tesla scanners. The FBIRN Phase 2 and Phase 3 datasets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN’s multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data. PMID:26364863

A Survey of the Job Profiles of Biomedical Informatics Graduates.

PubMed

Macedo, Alessandra A; Ruiz, Evandro E S; Baranauskas, José A

2016-10-17

In 2003, the University of São Paulo established the first Biomedical Informatics (BMI) undergraduate course in Brazil. Our mission is to provide undergraduate students with formal education on the fundamentals of BMI and its applied methods. This undergraduate course offers theoretical aspects, practical knowledge and scientifically oriented skills in the area of BMI, enab- ling students to contribute to research and methodical development in BMI. Course coordinators, professors and students frequently evaluate the BMI course and the curriculum to ensure that alumni receive quality higher education. This study investigates (i) the main job activities undertake by USP BMI graduates, (ii) subjects that are fundamental important for graduates to pursue a career in BMI, and (iii) the course quality perceived by the alumni. Use of a structured questionnaire to conduct a survey involving all the BMI graduates who received their Bachelor degree before July, 2015 (attempted n = 205). One hundred and forty-five graduates (71 %) answered the questionnaire. Nine out of ten of our former students currently work as informaticians. Seventy-six graduates (52 %) work within the biomedical informatics field. Fifty-five graduates (38 %) work outside the biomedical informatics field, but they work in other IT areas. Ten graduates (7 %) do not work with BMI or any other informatics activities, and four (3 %) are presently unemployed. Among the 145 surveyed BMI graduates, 46 (32 %) and seven (5 %) hold a Master's degree and a PhD degree, respectively. Database Systems, Software Engineering, Introduction to Computer Science, Object-Oriented Programming, and Data Structures are regarded as the most important subjects during the higher education course. The majority of the graduates (105 or 72 %) are satisfied with the BMI education and training they received during the undergraduate course. More than half of the graduates from our BMI course work in their primary education area. Besides technical adequacy, the diverse job profiles, and the high level of satisfaction of our graduates indicate the importance of undergraduate courses specialized in the BMI domain are of utmost importance.

Women in biomedical engineering and health informatics.

PubMed

McGregor, Carolyn; Frize, Monique

2008-01-01

A valuable session for anyone whether student or not, interested in learning more about Biomedical Engineering and Health Informatics as a career choice for women. Prominent women within the domains Biomedical Engineering and Health Informatics will present their research and their humanitarian interests that motivate them. Utilise the fantastic networking opportunity that will conclude this session to build and establish new professional networks with other women interested in your fields of expertise. Bring your contact details and be ready to make new contacts that are relevant for you.

Informatics for Metabolomics.

PubMed

Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

2016-01-01

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

Biomedical and Health Informatics Education – the IMIA Years

PubMed Central

2016-01-01

Summary Objective This paper presents the development of medical informatics education during the years from the establishment of the International Medical Informatics Association (IMIA) until today. Method A search in the literature was performed using search engines and appropriate keywords as well as a manual selection of papers. The search covered English language papers and was limited to search on papers title and abstract only. Results The aggregated papers were analyzed on the basis of the subject area, origin, time span, and curriculum development, and conclusions were drawn. Conclusions From the results, it is evident that IMIA has played a major role in comparing and integrating the Biomedical and Health Informatics educational efforts across the different levels of education and the regional distribution of educators and institutions. A large selection of references is presented facilitating future work on the field of education in biomedical and health informatics. PMID:27488405

AMIA Board white paper: definition of biomedical informatics and specification of core competencies for graduate education in the discipline

PubMed Central

Kulikowski, Casimir A; Shortliffe, Edward H; Currie, Leanne M; Elkin, Peter L; Hunter, Lawrence E; Johnson, Todd R; Kalet, Ira J; Lenert, Leslie A; Musen, Mark A; Ozbolt, Judy G; Smith, Jack W; Tarczy-Hornoch, Peter Z

2012-01-01

The AMIA biomedical informatics (BMI) core competencies have been designed to support and guide graduate education in BMI, the core scientific discipline underlying the breadth of the field's research, practice, and education. The core definition of BMI adopted by AMIA specifies that BMI is ‘the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.’ Application areas range from bioinformatics to clinical and public health informatics and span the spectrum from the molecular to population levels of health and biomedicine. The shared core informatics competencies of BMI draw on the practical experience of many specific informatics sub-disciplines. The AMIA BMI analysis highlights the central shared set of competencies that should guide curriculum design and that graduate students should be expected to master. PMID:22683918

Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey

PubMed Central

Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan

2013-01-01

The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259

The Function Biomedical Informatics Research Network Data Repository.

PubMed

Keator, David B; van Erp, Theo G M; Turner, Jessica A; Glover, Gary H; Mueller, Bryon A; Liu, Thomas T; Voyvodic, James T; Rasmussen, Jerod; Calhoun, Vince D; Lee, Hyo Jong; Toga, Arthur W; McEwen, Sarah; Ford, Judith M; Mathalon, Daniel H; Diaz, Michele; O'Leary, Daniel S; Jeremy Bockholt, H; Gadde, Syam; Preda, Adrian; Wible, Cynthia G; Stern, Hal S; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G

2016-01-01

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data. Copyright © 2015 Elsevier Inc. All rights reserved.

Big data science: A literature review of nursing research exemplars.

PubMed

Westra, Bonnie L; Sylvia, Martha; Weinfurter, Elizabeth F; Pruinelli, Lisiane; Park, Jung In; Dodd, Dianna; Keenan, Gail M; Senk, Patricia; Richesson, Rachel L; Baukner, Vicki; Cruz, Christopher; Gao, Grace; Whittenburg, Luann; Delaney, Connie W

Big data and cutting-edge analytic methods in nursing research challenge nurse scientists to extend the data sources and analytic methods used for discovering and translating knowledge. The purpose of this study was to identify, analyze, and synthesize exemplars of big data nursing research applied to practice and disseminated in key nursing informatics, general biomedical informatics, and nursing research journals. A literature review of studies published between 2009 and 2015. There were 650 journal articles identified in 17 key nursing informatics, general biomedical informatics, and nursing research journals in the Web of Science database. After screening for inclusion and exclusion criteria, 17 studies published in 18 articles were identified as big data nursing research applied to practice. Nurses clearly are beginning to conduct big data research applied to practice. These studies represent multiple data sources and settings. Although numerous analytic methods were used, the fundamental issue remains to define the types of analyses consistent with big data analytic methods. There are needs to increase the visibility of big data and data science research conducted by nurse scientists, further examine the use of state of the science in data analytics, and continue to expand the availability and use of a variety of scientific, governmental, and industry data resources. A major implication of this literature review is whether nursing faculty and preparation of future scientists (PhD programs) are prepared for big data and data science. Copyright © 2016 Elsevier Inc. All rights reserved.

Data Analysis and Data Mining: Current Issues in Biomedical Informatics

PubMed Central

Bellazzi, Riccardo; Diomidous, Marianna; Sarkar, Indra Neil; Takabayashi, Katsuhiko; Ziegler, Andreas; McCray, Alexa T.

2011-01-01

Summary Background Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. Objectives To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. Methods On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, that reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. Results The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. Conclusions Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers. PMID:22146916

Audacious goals for health and biomedical informatics in the new millennium.

PubMed

Greenes, R A; Lorenzi, N M

1998-01-01

The 1998 Scientific Symposium of the American College of Medical Informatics (ACMI) was devoted to developing visions for the future of health care and biomedicine and a strategic agenda for health and biomedical informatics in support of those visions. This symposium focus was prompted by the many major changes currently underway in health care delivery, education, and research, as well as in our health and biomedical enterprises, and by the constantly increasing role of information technology in both shaping and enabling these changes. The three audacious goals developed for 2008 are a virtual health care databank, a national health care knowledge base, and a personal clinical health record.

Design of e-Science platform for biomedical imaging research cross multiple academic institutions and hospitals

NASA Astrophysics Data System (ADS)

Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Ling, Tonghui; Wang, Tusheng; Wang, Mingqing; Hu, Haibo; Xu, Xuemin

2012-02-01

More and more image informatics researchers and engineers are considering to re-construct imaging and informatics infrastructure or to build new framework to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment. In this presentation, we show an outline and our preliminary design work of building an e-Science platform for biomedical imaging and informatics research and application in Shanghai. We will present our consideration and strategy on designing this platform, and preliminary results. We also will discuss some challenges and solutions in building this platform.

Designing Biomedical Informatics Infrastructure for Clinical and Translational Science

ERIC Educational Resources Information Center

La Paz Lillo, Ariel Isaac

2009-01-01

Clinical and Translational Science (CTS) rests largely on information flowing smoothly at multiple levels, in multiple directions, across multiple locations. Biomedical Informatics (BI) is seen as a backbone that helps to manage information flows for the translation of knowledge generated and stored in silos of basic science into bedside…

Computer Science, Biology and Biomedical Informatics academy: Outcomes from 5 years of Immersing High-school Students into Informatics Research.

PubMed

King, Andrew J; Fisher, Arielle M; Becich, Michael J; Boone, David N

2017-01-01

The University of Pittsburgh's Department of Biomedical Informatics and Division of Pathology Informatics created a Science, Technology, Engineering, and Mathematics (STEM) pipeline in 2011 dedicated to providing cutting-edge informatics research and career preparatory experiences to a diverse group of highly motivated high-school students. In this third editorial installment describing the program, we provide a brief overview of the pipeline, report on achievements of the past scholars, and present results from self-reported assessments by the 2015 cohort of scholars. The pipeline continues to expand with the 2015 addition of the innovation internship, and the introduction of a program in 2016 aimed at offering first-time research experiences to undergraduates who are underrepresented in pathology and biomedical informatics. Achievements of program scholars include authorship of journal articles, symposium and summit presentations, and attendance at top 25 universities. All of our alumni matriculated into higher education and 90% remain in STEM majors. The 2015 high-school program had ten participating scholars who self-reported gains in confidence in their research abilities and understanding of what it means to be a scientist.

Computer Science, Biology and Biomedical Informatics academy: Outcomes from 5 years of Immersing High-school Students into Informatics Research

PubMed Central

King, Andrew J.; Fisher, Arielle M.; Becich, Michael J.; Boone, David N.

2017-01-01

The University of Pittsburgh's Department of Biomedical Informatics and Division of Pathology Informatics created a Science, Technology, Engineering, and Mathematics (STEM) pipeline in 2011 dedicated to providing cutting-edge informatics research and career preparatory experiences to a diverse group of highly motivated high-school students. In this third editorial installment describing the program, we provide a brief overview of the pipeline, report on achievements of the past scholars, and present results from self-reported assessments by the 2015 cohort of scholars. The pipeline continues to expand with the 2015 addition of the innovation internship, and the introduction of a program in 2016 aimed at offering first-time research experiences to undergraduates who are underrepresented in pathology and biomedical informatics. Achievements of program scholars include authorship of journal articles, symposium and summit presentations, and attendance at top 25 universities. All of our alumni matriculated into higher education and 90% remain in STEM majors. The 2015 high-school program had ten participating scholars who self-reported gains in confidence in their research abilities and understanding of what it means to be a scientist. PMID:28400991

Foundational biomedical informatics research in the clinical and translational science era: a call to action.

PubMed

Payne, Philip R O; Embi, Peter J; Niland, Joyce

2010-01-01

Advances in clinical and translational science, along with related national-scale policy and funding mechanisms, have provided significant opportunities for the advancement of applied clinical research informatics (CRI) and translational bioinformatics (TBI). Such efforts are primarily oriented to application and infrastructure development and are critical to the conduct of clinical and translational research. However, they often come at the expense of the foundational CRI and TBI research needed to grow these important biomedical informatics subdisciplines and ensure future innovations. In light of this challenge, it is critical that a number of steps be taken, including the conduct of targeted advocacy campaigns, the development of community-accepted research agendas, and the continued creation of forums for collaboration and knowledge exchange. Such efforts are needed to ensure that the biomedical informatics community is able to advance CRI and TBI science in the context of the modern clinical and translational science era.

Multicenter breast cancer collaborative registry.

PubMed

Sherman, Simon; Shats, Oleg; Fleissner, Elizabeth; Bascom, George; Yiee, Kevin; Copur, Mehmet; Crow, Kate; Rooney, James; Mateen, Zubeena; Ketcham, Marsha A; Feng, Jianmin; Sherman, Alexander; Gleason, Michael; Kinarsky, Leo; Silva-Lopez, Edibaldo; Edney, James; Reed, Elizabeth; Berger, Ann; Cowan, Kenneth

2011-01-01

The Breast Cancer Collaborative Registry (BCCR) is a multicenter web-based system that efficiently collects and manages a variety of data on breast cancer (BC) patients and BC survivors. This registry is designed as a multi-tier web application that utilizes Java Servlet/JSP technology and has an Oracle 11g database as a back-end. The BCCR questionnaire has accommodated standards accepted in breast cancer research and healthcare. By harmonizing the controlled vocabulary with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), the BCCR provides a standardized approach to data collection and reporting. The BCCR has been recently certified by the National Cancer Institute's Center for Biomedical Informatics and Information Technology (NCI CBIIT) as a cancer Biomedical Informatics Grid (caBIG(®)) Bronze Compatible product.The BCCR is aimed at facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention, treatment, and survivorship strategies against breast cancer. Currently, seven cancer institutions are participating in the BCCR that contains data on almost 900 subjects (BC patients and survivors, as well as individuals at high risk of getting BC).

Multicenter Breast Cancer Collaborative Registry

PubMed Central

Sherman, Simon; Shats, Oleg; Fleissner, Elizabeth; Bascom, George; Yiee, Kevin; Copur, Mehmet; Crow, Kate; Rooney, James; Mateen, Zubeena; Ketcham, Marsha A.; Feng, Jianmin; Sherman, Alexander; Gleason, Michael; Kinarsky, Leo; Silva-Lopez, Edibaldo; Edney, James; Reed, Elizabeth; Berger, Ann; Cowan, Kenneth

2011-01-01

The Breast Cancer Collaborative Registry (BCCR) is a multicenter web-based system that efficiently collects and manages a variety of data on breast cancer (BC) patients and BC survivors. This registry is designed as a multi-tier web application that utilizes Java Servlet/JSP technology and has an Oracle 11g database as a back-end. The BCCR questionnaire has accommodated standards accepted in breast cancer research and healthcare. By harmonizing the controlled vocabulary with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), the BCCR provides a standardized approach to data collection and reporting. The BCCR has been recently certified by the National Cancer Institute’s Center for Biomedical Informatics and Information Technology (NCI CBIIT) as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product. The BCCR is aimed at facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention, treatment, and survivorship strategies against breast cancer. Currently, seven cancer institutions are participating in the BCCR that contains data on almost 900 subjects (BC patients and survivors, as well as individuals at high risk of getting BC). PMID:21918596

Big Data: Are Biomedical and Health Informatics Training Programs Ready? Contribution of the IMIA Working Group for Health and Medical Informatics Education.

PubMed

Otero, P; Hersh, W; Jai Ganesh, A U

2014-08-15

The growing volume and diversity of health and biomedical data indicate that the era of Big Data has arrived for healthcare. This has many implications for informatics, not only in terms of implementing and evaluating information systems, but also for the work and training of informatics researchers and professionals. This article addresses the question: What do biomedical and health informaticians working in analytics and Big Data need to know? We hypothesize a set of skills that we hope will be discussed among academic and other informaticians. The set of skills includes: Programming - especially with data-oriented tools, such as SQL and statistical programming languages; Statistics - working knowledge to apply tools and techniques; Domain knowledge - depending on one's area of work, bioscience or health care; and Communication - being able to understand needs of people and organizations, and articulate results back to them. Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in "deep analytical talent" as well as those who need knowledge to support such individuals.

76 FR 24889 - Submission for OMB Review; Comment Request; Cancer Biomedical Informatics Grid® (caBIG®) Support...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-03

... the Office of Management and Budget (OMB) a request to review and approve the information collection...: The NCI Center for Biomedical Informatics and Information Technology (CBIIT) launched the enterprise...] Enterprise Support Network (ESN), including the caBIG [supreg] Support Service Provider (SSP) Program. The ca...

Trends in biomedical informatics: most cited topics from recent years

PubMed Central

Kim, Hyeon-Eui; Jiang, Xiaoqian; Kim, Jihoon

2011-01-01

Biomedical informatics is a young, highly interdisciplinary field that is evolving quickly. It is important to know which published topics in generalist biomedical informatics journals elicit the most interest from the scientific community, and whether this interest changes over time, so that journals can better serve their readers. It is also important to understand whether free access to biomedical informatics articles impacts their citation rates in a significant way, so authors can make informed decisions about unlock fees, and journal owners and publishers understand the implications of open access. The topics and JAMIA articles from years 2009 and 2010 that have been most cited according to the Web of Science are described. To better understand the effects of free access in article dissemination, the number of citations per month after publication for articles published in 2009 versus 2010 was compared, since there was a significant change in free access to JAMIA articles between those years. Results suggest that there is a positive association between free access and citation rate for JAMIA articles. PMID:22180873

Cognitive and learning sciences in biomedical and health instructional design: A review with lessons for biomedical informatics education.

PubMed

Patel, Vimla L; Yoskowitz, Nicole A; Arocha, Jose F; Shortliffe, Edward H

2009-02-01

Theoretical and methodological advances in the cognitive and learning sciences can greatly inform curriculum and instruction in biomedicine and also educational programs in biomedical informatics. It does so by addressing issues such as the processes related to comprehension of medical information, clinical problem-solving and decision-making, and the role of technology. This paper reviews these theories and methods from the cognitive and learning sciences and their role in addressing current and future needs in designing curricula, largely using illustrative examples drawn from medical education. The lessons of this past work are also applicable, however, to biomedical and health professional curricula in general, and to biomedical informatics training, in particular. We summarize empirical studies conducted over two decades on the role of memory, knowledge organization and reasoning as well as studies of problem-solving and decision-making in medical areas that inform curricular design. The results of this research contribute to the design of more informed curricula based on empirical findings about how people learn and think, and more specifically, how expertise is developed. Similarly, the study of practice can also help to shape theories of human performance, technology-based learning, and scientific and professional collaboration that extend beyond the domain of medicine. Just as biomedical science has revolutionized health care practice, research in the cognitive and learning sciences provides a scientific foundation for education in biomedicine, the health professions, and biomedical informatics.

Biomedical informatics publications: a global perspective: part I: conferences.

PubMed

Maojo, V; García-Remesal, M; Bielza, C; Crespo, J; Perez-Rey, D; Kulikowski, C

2012-01-01

In the past decade, Medical Informatics (MI) and Bioinformatics (BI) have converged towards a new discipline, called Biomedical Informatics (BMI) bridging informatics methods across the spectrum from genomic research to personalized medicine and global healthcare. This convergence still raises challenging research questions which are being addressed by researchers internationally, which in turn raises the question of how biomedical informatics publications reflect the contributions from around the world in documenting the research. To analyse the worldwide participation of biomedical informatics researchers from professional groups and societies in the best-known scientific conferences in the field. The analysis is focused on their geographical affiliation, but also includes other features, such as the impact and recognition of the conferences. We manually collected data about authors of papers presented at three major MI conferences: Medinfo, MIE and the AMIA symposium. In addition, we collected data from a BI conference, ISMB, as a comparison. Finally, we analyzed the impact and recognition of these conferences within their scientific contexts. Data indicate a predominance of local authors at the regional conferences (AMIA and MIE), whereas other conferences with a world-wide scope (Medinfo and ISMB) had broader participation. Our analysis shows that the influence of these conferences beyond the discipline remains somewhat limited. Our results suggest that for BMI to be recognized as a broad discipline, both in the geographical and scientific sense, it will need to extend the scope of collaborations and their interdisciplinary impacts worldwide.

The World Wide Web: a review of an emerging internet-based technology for the distribution of biomedical information.

PubMed Central

Lowe, H J; Lomax, E C; Polonkey, S E

1996-01-01

The Internet is rapidly evolving from a resource used primarily by the research community to a true global information network offering a wide range of databases and services. This evolution presents many opportunities for improved access to biomedical information, but Internet-based resources have often been difficult for the non-expert to develop and use. The World Wide Web (WWW) supports an inexpensive, easy-to-use, cross-platform, graphic interface to the Internet that may radically alter the way we retrieve and disseminate medical data. This paper summarizes the Internet and hypertext origins of the WWW, reviews WWW-specific technologies, and describes current and future applications of this technology in medicine and medical informatics. The paper also includes an appendix of useful biomedical WWW servers. PMID:8750386

Multiscale Integration of -Omic, Imaging, and Clinical Data in Biomedical Informatics

PubMed Central

Phan, John H.; Quo, Chang F.; Cheng, Chihwen; Wang, May Dongmei

2016-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data. PMID:23231990

Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

PubMed

Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

2012-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

Big Data Application in Biomedical Research and Health Care: A Literature Review.

PubMed

Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

2016-01-01

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.

Big Data Application in Biomedical Research and Health Care: A Literature Review

PubMed Central

Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

2016-01-01

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care. PMID:26843812

Genomic Data Commons and Genomic Cloud Pilots - Google Hangout

Cancer.gov

Join us for a live, moderated discussion about two NCI efforts to expand access to cancer genomics data: the Genomic Data Commons and Genomic Cloud Pilots. NCI subject matters experts will include Louis M. Staudt, M.D., Ph.D., Director Center for Cancer Genomics, Warren Kibbe, Ph.D., Director, NCI Center for Biomedical Informatics and Information Technology, and moderated by Anthony Kerlavage, Ph.D., Chief, Cancer Informatics Branch, Center for Biomedical Informatics and Information Technology. We welcome your questions before and during the Hangout on Twitter using the hashtag #AskNCI.

Semantic SenseLab: implementing the vision of the Semantic Web in neuroscience

PubMed Central

Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

2011-01-01

Summary Objective Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Methods Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. Conclusion We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/ PMID:20006477

Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

PubMed

Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

2010-01-01

Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

Mediator infrastructure for information integration and semantic data integration environment for biomedical research.

PubMed

Grethe, Jeffrey S; Ross, Edward; Little, David; Sanders, Brian; Gupta, Amarnath; Astakhov, Vadim

2009-01-01

This paper presents current progress in the development of semantic data integration environment which is a part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A goal is the development of a cyberinfrastructure for biomedical research that supports advance data acquisition, data storage, data management, data integration, data mining, data visualization, and other computing and information processing services over the Internet. Each participating institution maintains storage of their experimental or computationally derived data. Mediator-based data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This paper describes recent revision of the system architecture, implementation, and capabilities of the semantically based data integration environment for BIRN.

Commentaries on “Informatics and Medicine: From Molecules to Populations”

PubMed Central

Altman, R. B.; Balling, R.; Brinkley, J. F.; Coiera, E.; Consorti, F.; Dhansay, M. A.; Geissbuhler, A.; Hersh, W.; Kwankam, S. Y.; Lorenzi, N. M.; Martin-Sanchez, F.; Mihalas, G. I.; Shahar, Y.; Takabayashi, K.; Wiederhold, G.

2009-01-01

Summary Objective To discuss interdisciplinary research and education in the context of informatics and medicine by commenting on the paper of Kuhn et al. “Informatics and Medicine: From Molecules to Populations”. Method Inviting an international group of experts in biomedical and health informatics and related disciplines to comment on this paper. Results and Conclusions The commentaries include a wide range of reasoned arguments and original position statements which, while strongly endorsing the educational needs identified by Kuhn et al., also point out fundamental challenges that are very specific to the unusual combination of scientific, technological, personal and social problems characterizing biomedical informatics. They point to the ultimate objectives of managing difficult human health problems, which are unlikely to yield to technological solutions alone. The psychological, societal, and environmental components of health and disease are emphasized by several of the commentators, setting the stage for further debate and constructive suggestions. PMID:18690363

Informatics and Technology in Resident Education.

PubMed

Niehaus, William

2017-05-01

Biomedical or clinical informatics is the transdisciplinary field that studies and develops effective uses of biomedical data, information technology innovations, and medical knowledge for scientific inquiry, problem solving, and decision making, with an emphasis on improving human health. Given the ongoing advances in information technology, the field of informatics is becoming important to clinical practice and to residency education. This article will discuss how informatics is specifically relevant to residency education and the different ways to incorporate informatics into residency education, and will highlight applications of current technology in the context of residency education. How informatics can optimize communication for residents, promote information technology use, refine documentation techniques, reduce medical errors, and improve clinical decision making will be reviewed. It is hoped that this article will increase faculty and trainees' knowledge of the field of informatics, awareness of available technology, and will assist practitioners to maximize their ability to provide quality care to their patients. This article will also introduce the idea of incorporating informatics specialists into residency programs to help practitioners deliver more evidenced-based care and to further improve their efficiency. Copyright © 2017 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

The diversity and disparity in biomedical informatics (DDBI) workshop.

PubMed

Southerland, William M; Swamidass, S Joshua; Payne, Philip R O; Wiley, Laura; Williams-DeVane, ClarLynda

2018-01-01

The Diversity and Disparity in Biomedical Informatics (DDBI) workshop will be focused on complementary and critical issues concerned with enhancing diversity in the informatics workforce as well as diversity in patient cohorts. According to the National Institute of Minority Health and Health Disparities (NIMHD) at the NIH, diversity refers to the inclusion of the following traditionally underrepresented groups: African Americans/Blacks, Asians (>30 countries), American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Latino or Hispanic (20 countries). Gender, culture, and socioeconomic status are also important dimensions of diversity, which may define some underrepresented groups. The under-representation of specific groups in both the biomedical informatics workforce as well as in the patient-derived data that is being used for research purposes has contributed to an ongoing disparity; these groups have not experienced equity in contributing to or benefiting from advancements in informatics research. This workshop will highlight innovative efforts to increase the pool of minority informaticians and discuss examples of informatics research that addresses the health concerns that impact minority populations. This workshop topics will provide insight into overcoming pipeline issues in the development of minority informaticians while emphasizing the importance of minority participation in health related research. The DDBI workshop will occur in two parts. Part I will discuss specific minority health & health disparities research topics and Part II will cover discussions related to overcoming pipeline issues in the training of minority informaticians.

Gaps in the existing public health informatics training programs: a challenge to the development of a skilled global workforce.

PubMed

Joshi, Ashish; Perin, Douglas Marcel Puricelli

2012-01-01

The objective of this study was to explore public health informatics (PHI) training programs that currently exist to meet the growing demand for a trained global workforce. We used several search engines, scientific databases, and the websites of informatics organizations; sources included PubMed, Google, the American Medical Informatics Organization, and the International Medical Informatics Organization. The search was conducted from May to July 2011 and from January to February 2012 using key words such as informatics, public health informatics, or biomedical informatics along with academic programs, training, certificate, graduate programs, or postgraduate programs. Course titles and catalog descriptions were gathered from the program or institution websites. Variables included PHI program categories, location and mode of delivery, program credits, and costs. Each course was then categorized based on its title and description as available on the Internet. Finally, we matched course titles and descriptions with the competencies for PHIs determined by Centers for Disease Control and Prevention (CDC). Descriptive analysis was performed to report means and frequency distributions for continuous and categorical variables. Stratified analysis was performed to explore average credits and cost per credit among both the public and private institutions. Fifteen PHI programs were identified across 13 different institutions, the majority of which were US-based. The average number of credits and the associated costs required to obtain PHI training were much higher in private as compared to public institutions. The study results suggest that a need for online contextual and cost-effective PHI training programs exists to address the growing needs of professionals worldwide who are using technology to improve public health in their respective countries.

Facilitating biomedical researchers' interrogation of electronic health record data: Ideas from outside of biomedical informatics.

PubMed

Hruby, Gregory W; Matsoukas, Konstantina; Cimino, James J; Weng, Chunhua

2016-04-01

Electronic health records (EHR) are a vital data resource for research uses, including cohort identification, phenotyping, pharmacovigilance, and public health surveillance. To realize the promise of EHR data for accelerating clinical research, it is imperative to enable efficient and autonomous EHR data interrogation by end users such as biomedical researchers. This paper surveys state-of-art approaches and key methodological considerations to this purpose. We adapted a previously published conceptual framework for interactive information retrieval, which defines three entities: user, channel, and source, by elaborating on channels for query formulation in the context of facilitating end users to interrogate EHR data. We show the current progress in biomedical informatics mainly lies in support for query execution and information modeling, primarily due to emphases on infrastructure development for data integration and data access via self-service query tools, but has neglected user support needed during iteratively query formulation processes, which can be costly and error-prone. In contrast, the information science literature has offered elaborate theories and methods for user modeling and query formulation support. The two bodies of literature are complementary, implying opportunities for cross-disciplinary idea exchange. On this basis, we outline the directions for future informatics research to improve our understanding of user needs and requirements for facilitating autonomous interrogation of EHR data by biomedical researchers. We suggest that cross-disciplinary translational research between biomedical informatics and information science can benefit our research in facilitating efficient data access in life sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

Big Data: Are Biomedical and Health Informatics Training Programs Ready?

PubMed Central

Hersh, W.; Ganesh, A. U. Jai

2014-01-01

Summary Objectives The growing volume and diversity of health and biomedical data indicate that the era of Big Data has arrived for healthcare. This has many implications for informatics, not only in terms of implementing and evaluating information systems, but also for the work and training of informatics researchers and professionals. This article addresses the question: What do biomedical and health informaticians working in analytics and Big Data need to know? Methods We hypothesize a set of skills that we hope will be discussed among academic and other informaticians. Results The set of skills includes: Programming - especially with data-oriented tools, such as SQL and statistical programming languages; Statistics - working knowledge to apply tools and techniques; Domain knowledge - depending on one’s area of work, bioscience or health care; and Communication - being able to understand needs of people and organizations, and articulate results back to them. Conclusions Biomedical and health informatics educational programs must introduce concepts of analytics, Big Data, and the underlying skills to use and apply them into their curricula. The development of new coursework should focus on those who will become experts, with training aiming to provide skills in “deep analytical talent” as well as those who need knowledge to support such individuals. PMID:25123740

Introducing Kuhn et al.'s paper "Informatics and medicine: from molecules to populations" and invited papers on this special topic.

PubMed

Kulikowski, C A

2008-01-01

To introduce the paper by Kuhn et al. "Informatics and Medicine: From Molecules to Populations" and the papers that follow on this special topic in this issue of Methods of Information in Medicine, which opens a debate on the Kuhn et al. paper's assertions by an international panel of invited researchers in biomedical informatics. An introductory summary and comparative review of the Kuhn et al. paper and the debate papers, with some personal observations. The Kuhn et al. paper makes a strong case for interdisciplinary education in biomedical informatics across institutions at the graduate level, which could be strengthened by analysis of previous relevant interdisciplinary experiences elsewhere, and the challenges they have faced, which point to more pervasive and earlier-stage needs for both education and practice bridging the research and healthcare communities. The experts debating the Kuhn et al. paper strongly and broadly support the key recommendation of developing graduate education in biomedical informatics in a more comprehensive way, yet at the same time make some incisive comments about the limitations of the "positivistic" and excessively technological orientation of the paper, which could benefit from greater attention to the narrative and care-giving aspects of health practice, with more emphasis on its human and social aspects.

eHealth and IMIA's Strategic Planning Process - IMIA conference introductory address.

PubMed

Murray, Peter; Haux, Reinhold; Lorenzi, Nancy

2008-01-01

The International Medical Informatics Association (IMIA) is the only organization in health and biomedical informatics which is fully international in scope, bridging the academic, health practice, education, and health industry worlds through conferences, working groups, special interest groups and publications. Authored by the IMIA Interim Vice President for Strategic Planning Implementation and co-authored by the current IMIA President and the IMIA Past-President, the intention of this paper is to introduce IMIA's current strategic planning process and to set this process in relation to 'eHealth: Combining Health Telematics, Telemedicine, Biomedical Engineering and Bioinformatics to the Edge', the theme of this conference. From the viewpoint of an international organization such as IMIA, an eHealth strategy needs to be considered in a comprehensive way, including broadly stimulating high-quality health and biomedical informatics research and education, as well as providing support to bridging outcomes towards a new practice of health care in a changing world.

[Integration of clinical and biological data in clinical practice using bioinformatics].

PubMed

Coltell, Oscar; Arregui, María; Fabregat, Antonio; Portolés, Olga

2008-05-01

The aim of our work is to describe essential aspects of Medical Informatics, Bioinformatics and Biomedical Informatics, that are used in biomedical research and clinical practice. These disciplines have emerged from the need to find new scientific and technical approaches to manage, store, analyze and report data generated in clinical practice and molecular biology and other medical specialties. It can be also useful to integrate research information generated in different areas of health care. Moreover, these disciplines are interdisciplinary and integrative, two key features not shared by other areas of medical knowledge. Finally, when Bioinformatics and Biomedical Informatics approach to medical investigation and practice are applied, a new discipline, called Clinical Bioinformatics, emerges. The latter requires a specific training program to create a new professional profile. We have not been able to find a specific training program in Clinical Bioinformatics in Spain.

Reflections on biomedical informatics: from cybernetics to genomic medicine and nanomedicine.

PubMed

Maojo, Victor; Kulikowski, Casimir A

2006-01-01

Expanding on our previous analysis of Biomedical Informatics (BMI), the present perspective ranges from cybernetics to nanomedicine, based on its scientific, historical, philosophical, theoretical, experimental, and technological aspects as they affect systems developments, simulation and modelling, education, and the impact on healthcare. We then suggest that BMI is still searching for strong basic scientific principles around which it can crystallize. As -omic biological knowledge increasingly impacts the future of medicine, ubiquitous computing and informatics become even more essential, not only for the technological infrastructure, but as a part of the scientific enterprise itself. The Virtual Physiological Human and investigations into nanomedicine will surely produce yet more unpredictable opportunities, leading to significant changes in biomedical research and practice. As a discipline involved in making such advances possible, BMI is likely to need to re-define itself and extend its research horizons to meet the new challenges.

DEVELOPMENT AND INSTITUTIONALIZATION OF THE FIRST ONLINE CERTIFICATE AND MASTER PROGRAM OF BIOMEDICAL INFORMATICS IN GLOBAL HEALTH IN PERU

PubMed Central

García, Patricia J.; Egoavil, Miguel S.; Blas, Magaly M.; Alvarado-Vásquez, Eduardo; Curioso, Walter H.; Zimic, Mirko; Castagnetto, Jesus M.; Lescano, Andrés G.; Lopez, Diego M.; Cárcamo, Cesar P.

2017-01-01

Training in Biomedical Informatics is essential to meet the challenges of a globalized world. However, the development of postgraduate training and research programs in this area are scarce in Latin America. Through QUIPU: Andean Center for Training and research in Iformatics for Global Health, has developed the first Certificate and Master’s Program on Biomedical Informatics in the Andean Region. The aim of this article is to describe the experience of the program. To date, 51 students from Peru, Chile, Ecuador, Colombia and Venezuela have participated; they come from health ministries, hospitals, universities, research centers, professional associations and private companies. Seventeen courses were offered with the participation of faculty from Argentina, Chile, Colombia, USA, Mexico and Peru. This program is already institutionalized at the School of Public Health and Administration from the Universidad Peruana Cayetano Heredia. PMID:26338399

Featured Article: Genotation: Actionable knowledge for the scientific reader

PubMed Central

Willis, Ethan; Sakauye, Mark; Jose, Rony; Chen, Hao; Davis, Robert L

2016-01-01

We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org. The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug–gene relationships, 5981 gene–disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge. PMID:26900164

Featured Article: Genotation: Actionable knowledge for the scientific reader.

PubMed

Nagahawatte, Panduka; Willis, Ethan; Sakauye, Mark; Jose, Rony; Chen, Hao; Davis, Robert L

2016-06-01

We present an article viewer application that allows a scientific reader to easily discover and share knowledge by linking genomics-related concepts to knowledge of disparate biomedical databases. High-throughput data streams generated by technical advancements have contributed to scientific knowledge discovery at an unprecedented rate. Biomedical Informaticists have created a diverse set of databases to store and retrieve the discovered knowledge. The diversity and abundance of such resources present biomedical researchers a challenge with knowledge discovery. These challenges highlight a need for a better informatics solution. We use a text mining algorithm, Genomine, to identify gene symbols from the text of a journal article. The identified symbols are supplemented with information from the GenoDB knowledgebase. Self-updating GenoDB contains information from NCBI Gene, Clinvar, Medgen, dbSNP, KEGG, PharmGKB, Uniprot, and Hugo Gene databases. The journal viewer is a web application accessible via a web browser. The features described herein are accessible on www.genotation.org The Genomine algorithm identifies gene symbols with an accuracy shown by .65 F-Score. GenoDB currently contains information regarding 59,905 gene symbols, 5633 drug-gene relationships, 5981 gene-disease relationships, and 713 pathways. This application provides scientific readers with actionable knowledge related to concepts of a manuscript. The reader will be able to save and share supplements to be visualized in a graphical manner. This provides convenient access to details of complex biological phenomena, enabling biomedical researchers to generate novel hypothesis to further our knowledge in human health. This manuscript presents a novel application that integrates genomic, proteomic, and pharmacogenomic information to supplement content of a biomedical manuscript and enable readers to automatically discover actionable knowledge. © 2016 by the Society for Experimental Biology and Medicine.

Uniform resolution of compact identifiers for biomedical data

PubMed Central

Wimalaratne, Sarala M.; Juty, Nick; Kunze, John; Janée, Greg; McMurry, Julie A.; Beard, Niall; Jimenez, Rafael; Grethe, Jeffrey S.; Hermjakob, Henning; Martone, Maryann E.; Clark, Tim

2018-01-01

Most biomedical data repositories issue locally-unique accessions numbers, but do not provide globally unique, machine-resolvable, persistent identifiers for their datasets, as required by publishers wishing to implement data citation in accordance with widely accepted principles. Local accessions may however be prefixed with a namespace identifier, providing global uniqueness. Such “compact identifiers” have been widely used in biomedical informatics to support global resource identification with local identifier assignment. We report here on our project to provide robust support for machine-resolvable, persistent compact identifiers in biomedical data citation, by harmonizing the Identifiers.org and N2T.net (Name-To-Thing) meta-resolvers and extending their capabilities. Identifiers.org services hosted at the European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), and N2T.net services hosted at the California Digital Library (CDL), can now resolve any given identifier from over 600 source databases to its original source on the Web, using a common registry of prefix-based redirection rules. We believe these services will be of significant help to publishers and others implementing persistent, machine-resolvable citation of research data. PMID:29737976

Trends in biomedical informatics: automated topic analysis of JAMIA articles.

PubMed

Han, Dong; Wang, Shuang; Jiang, Chao; Jiang, Xiaoqian; Kim, Hyeon-Eui; Sun, Jimeng; Ohno-Machado, Lucila

2015-11-01

Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a "generalist" journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods, Organization & Administration, and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Short Factography About IMIA and EFMI

PubMed Central

Hofdijk, Jacob; Weber, Patrick; Mantas, John; Mihalas, George; Masic, Izet

2014-01-01

International Medical Informatics Association (IMIA) and European Federation of Medical Informatics are scientific associations which represents Health/Medical informatics as scientific and profesional disciplines. Those associations have long tradition in spreading knowledge, experiences and strategies in organization, practical applications and education within Health, Medical and Biomedical informatics in approximately 60 countries the world. In this review we present basic facts about IMIA and EFMI.who celebrate this 50 years of their establishing as professional associations. PMID:24648623

Information Technology Education for Health Professionals: Opportunities and Challenges.

ERIC Educational Resources Information Center

Haque, Syed S.; Gibson, David M.

1998-01-01

Describes surveys of potential health-care employers and health-care professionals to identify the need for biomedical informatics programs. Outlines a certificate program, master of science in biomedicine and nursing informatics, and a Ph.D. program. (SK)

Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data

PubMed Central

Kibbe, Warren A.; Arze, Cesar; Felix, Victor; Mitraka, Elvira; Bolton, Evan; Fu, Gang; Mungall, Christopher J.; Binder, Janos X.; Malone, James; Vasant, Drashtti; Parkinson, Helen; Schriml, Lynn M.

2015-01-01

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years. These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protégé to curate DO in web ontology language. This will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning. PMID:25348409

[175 years of the National Library of Medicine, of the United States of America: a scientific and cultural treasure worthy of admiration].

PubMed

Cabello C, Felipe

2011-09-01

The National Library of Medicine (NLM) of the United States of America, celebrates in 2011 its 175th anniversary. This Library, the largest biomedical library in the world, has a proud and rich history serving the health community and the public, especially since its transfer to the National Institutes of Health in Bethesda, Maryland, in 1968. It holds 17 million publications in 150 languages, and has an important collection of ancient and modern historical books as well as original publications of Vesalius and other founders of biomedicine. Its modern document collections illustrate the progress of medical sciences. These collections include laboratory notes from many scientists whose work forms the foundations of contemporary life sciences. The Library also provides several services for health research and for the public, including databases and services such as MedLine and BLAST. The NLM constantly strives to fulfill the information needs of its customers, whether scientists or the public at large. For example, as the Hispanic population of the Unites States has increased in recent years, the NLM has made larger and larger amounts of data available in Spanish to fulfill the health information needs of this population. NLM programs train professionals in library science and biomedical informatics and link biomedical libraries of 18 academic centers throughout the United States. The NLM funds competitive grants for training at the Library, organizing short instruction courses about library science and informatics, and writing books on health related matters including the history of medicine and public health. The NLM is managed and maintained by an outstanding and farsighted group of professionals and dedicated support staff. Their focus on serving and reaching both the biomedical community and the public at large has been crucial to its development into a world icon of biomedical sciences, information technology and the humanities.

Recent trends in biomedical informatics: a study based on JAMIA articles

PubMed Central

Jiang, Xiaoqian; Tse, Krystal; Wang, Shuang; Doan, Son; Kim, Hyeoneui; Ohno-Machado, Lucila

2013-01-01

In a growing interdisciplinary field like biomedical informatics, information dissemination and citation trends are changing rapidly due to many factors. To understand these factors better, we analyzed the evolution of the number of articles per major biomedical informatics topic, download/online view frequencies, and citation patterns (using Web of Science) for articles published from 2009 to 2012 in JAMIA. The number of articles published in JAMIA increased significantly from 2009 to 2012, and there were some topic differences in the last 4 years. Medical Record Systems, Algorithms, and Methods are topic categories that are growing fast in several publications. We observed a significant correlation between download frequencies and the number of citations per month since publication for a given article. Earlier free availability of articles to non-subscribers was associated with a higher number of downloads and showed a trend towards a higher number of citations. This trend will need to be verified as more data accumulate in coming years. PMID:24214018

Acupuncture for treating sciatica: a systematic review protocol

PubMed Central

Qin, Zongshi; Liu, Xiaoxu; Yao, Qin; Zhai, Yanbing; Liu, Zhishun

2015-01-01

Introduction This systematic review aims to assess the effectiveness and safety of acupuncture for treating sciatica. Methods The following nine databases will be searched from their inception to 30 October 2014: MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials (CENTRAL), the Chinese Biomedical Literature Database (CBM), the Chinese Medical Current Content (CMCC), the Chinese Scientific Journal Database (VIP database), the Wan-Fang Database, the China National Knowledge Infrastructure (CNKI) and Citation Information by National Institute of Informatics (CiNii). Randomised controlled trials (RCTs) of acupuncture for sciatica in English, Chinese or Japanese without restriction of publication status will be included. Two researchers will independently undertake study selection, extraction of data and assessment of study quality. Meta-analysis will be conducted after screening of studies. Data will be analysed using risk ratio for dichotomous data, and standardised mean difference or weighted mean difference for continuous data. Dissemination This systematic review will be disseminated electronically through a peer-reviewed publication or conference presentations. Trial registration number PROSPERO CRD42014015001. PMID:25922105

Conceptual biology, hypothesis discovery, and text mining: Swanson's legacy.

PubMed

Bekhuis, Tanja

2006-04-03

Innovative biomedical librarians and information specialists who want to expand their roles as expert searchers need to know about profound changes in biology and parallel trends in text mining. In recent years, conceptual biology has emerged as a complement to empirical biology. This is partly in response to the availability of massive digital resources such as the network of databases for molecular biologists at the National Center for Biotechnology Information. Developments in text mining and hypothesis discovery systems based on the early work of Swanson, a mathematician and information scientist, are coincident with the emergence of conceptual biology. Very little has been written to introduce biomedical digital librarians to these new trends. In this paper, background for data and text mining, as well as for knowledge discovery in databases (KDD) and in text (KDT) is presented, then a brief review of Swanson's ideas, followed by a discussion of recent approaches to hypothesis discovery and testing. 'Testing' in the context of text mining involves partially automated methods for finding evidence in the literature to support hypothetical relationships. Concluding remarks follow regarding (a) the limits of current strategies for evaluation of hypothesis discovery systems and (b) the role of literature-based discovery in concert with empirical research. Report of an informatics-driven literature review for biomarkers of systemic lupus erythematosus is mentioned. Swanson's vision of the hidden value in the literature of science and, by extension, in biomedical digital databases, is still remarkably generative for information scientists, biologists, and physicians.

Sensor, signal, and image informatics - state of the art and current topics.

PubMed

Lehmann, T M; Aach, T; Witte, H

2006-01-01

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

Evaluation of relational and NoSQL database architectures to manage genomic annotations.

PubMed

Schulz, Wade L; Nelson, Brent G; Felker, Donn K; Durant, Thomas J S; Torres, Richard

2016-12-01

While the adoption of next generation sequencing has rapidly expanded, the informatics infrastructure used to manage the data generated by this technology has not kept pace. Historically, relational databases have provided much of the framework for data storage and retrieval. Newer technologies based on NoSQL architectures may provide significant advantages in storage and query efficiency, thereby reducing the cost of data management. But their relative advantage when applied to biomedical data sets, such as genetic data, has not been characterized. To this end, we compared the storage, indexing, and query efficiency of a common relational database (MySQL), a document-oriented NoSQL database (MongoDB), and a relational database with NoSQL support (PostgreSQL). When used to store genomic annotations from the dbSNP database, we found the NoSQL architectures to outperform traditional, relational models for speed of data storage, indexing, and query retrieval in nearly every operation. These findings strongly support the use of novel database technologies to improve the efficiency of data management within the biological sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

Trends in biomedical informatics: automated topic analysis of JAMIA articles

PubMed Central

Wang, Shuang; Jiang, Chao; Jiang, Xiaoqian; Kim, Hyeon-Eui; Sun, Jimeng; Ohno-Machado, Lucila

2015-01-01

Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a “generalist” journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods, Organization & Administration, and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years. PMID:26555018

Core informatics competencies for clinical and translational scientists: what do our customers and collaborators need to know?

PubMed Central

Valenta, Annette L; Meagher, Emma A; Tachinardi, Umberto

2016-01-01

Since the inception of the Clinical and Translational Science Award (CTSA) program in 2006, leaders in education across CTSA sites have been developing and updating core competencies for Clinical and Translational Science (CTS) trainees. By 2009, 14 competency domains, including biomedical informatics, had been identified and published. Since that time, the evolution of the CTSA program, changes in the practice of CTS, the rapid adoption of electronic health records (EHRs), the growth of biomedical informatics, the explosion of big data, and the realization that some of the competencies had proven to be difficult to apply in practice have made it clear that the competencies should be updated. This paper describes the process undertaken and puts forth a new set of competencies that has been recently endorsed by the Clinical Research Informatics Workgroup of AMIA. In addition to providing context and background for the current version of the competencies, we hope this will serve as a model for revision of competencies over time. PMID:27121608

XCEDE: An Extensible Schema For Biomedical Data

PubMed Central

Gadde, Syam; Aucoin, Nicole; Grethe, Jeffrey S.; Keator, David B.; Marcus, Daniel S.; Pieper, Steve

2013-01-01

The XCEDE (XML-based Clinical and Experimental Data Exchange) XML schema, developed by members of the BIRN (Biomedical Informatics Research Network), provides an extensive metadata hierarchy for storing, describing and documenting the data generated by scientific studies. Currently at version 2.0, the XCEDE schema serves as a specification for the exchange of scientific data between databases, analysis tools, and web services. It provides a structured metadata hierarchy, storing information relevant to various aspects of an experiment (project, subject, protocol, etc.). Each hierarchy level also provides for the storage of data provenance information allowing for a traceable record of processing and/or changes to the underlying data. The schema is extensible to support the needs of various data modalities and to express types of data not originally envisioned by the developers. The latest version of the XCEDE schema and manual are available from http://www.xcede.org/ PMID:21479735

Leveraging biomedical ontologies and annotation services to organize microbiome data from Mammalian hosts.

PubMed

Sarkar, Indra Neil

2010-11-13

A better understanding of commensal microbiotic communities ("microbiomes") may provide valuable insights to human health. Towards this goal, an essential step may be the development of approaches to organize data that can enable comparative hypotheses across mammalian microbiomes. The present study explores the feasibility of using existing biomedical informatics resources - especially focusing on those available at the National Center for Biomedical Ontology - to organize microbiome data contained within large sequence repositories, such as GenBank. The results indicate that the Foundational Model of Anatomy and SNOMED CT can be used to organize greater than 90% of the bacterial organisms associated with 10 domesticated mammalian species. The promising findings suggest that the current biomedical informatics infrastructure may be used towards the organizing of microbiome data beyond humans. Furthermore, the results identify key concepts that might be organized into a semantic structure for incorporation into subsequent annotations that could facilitate comparative biomedical hypotheses pertaining to human health.

Twenty Years of Society of Medical Informatics of B&H and the Journal Acta Informatica Medica

PubMed Central

Masic, Izet

2012-01-01

In 2012, Health/Medical informatics profession celebrates five jubilees in Bosnia and Herzegovina: a) Thirty five years from the introduction of the first automatic manipulation of data; b) Twenty five years from establishing Society for Medical Informatics BiH; c) Twenty years from establishing scientific and professional journal of the Society for Medical Informatics of Bosnia and Herzegovina „Acta Informatica Medica“; d) Twenty years from establishing first Cathdra for Medical Informatics on biomedical faculties in Bosnia and Herzegovina and e) Ten years from the introduction of “Distance learning” in medical curriculum. All of the five mentioned activities in the area of Medical informatics had special importance and gave appropriate contribution in the development of Health/Medical informatics in Bosnia And Herzegovina. PMID:23322947

Twenty years of society of medical informatics of b&h and the journal acta informatica medica.

PubMed

Masic, Izet

2012-03-01

In 2012, Health/Medical informatics profession celebrates five jubilees in Bosnia and Herzegovina: a) Thirty five years from the introduction of the first automatic manipulation of data; b) Twenty five years from establishing Society for Medical Informatics BiH; c) Twenty years from establishing scientific and professional journal of the Society for Medical Informatics of Bosnia and Herzegovina "Acta Informatica Medica"; d) Twenty years from establishing first Cathdra for Medical Informatics on biomedical faculties in Bosnia and Herzegovina and e) Ten years from the introduction of "Distance learning" in medical curriculum. All of the five mentioned activities in the area of Medical informatics had special importance and gave appropriate contribution in the development of Health/Medical informatics in Bosnia And Herzegovina.

Informatics for Peru in the new millennium.

PubMed

Karras, B T; Kimball, A M; Gonzales, V; Pautler, N A; Alarcón, J; Garcia, P J; Fuller, S

2001-01-01

As efforts continue to narrow the digital divide between the North and South, a new biomedical and health informatics training effort has been launched in Peru. This report describes the first year of work on this collaborative effort between the University of Washington (Seattle) Universidad Peruana Cayetano Heredia and Universidad Nacional de San Marcos (Peru) To describe activities in the first year of a new International Research and Training Program in Biomedical and Health Informatics. Descriptive analysis of key activities including an assessment of electronic environment through observation and survey, an in country short course with quantitative evaluation, and first round of recruitment of Peruvian scholars for long-term training in Seattle. A two-week short course on informatics was held in the country. Participants' success in learning was demonstrated through pretest/posttest. A systematic assessment of electronic environment in Peru was carried out and two scholars for long-term training were enrolled at the University of Washington, Seattle. Initial activity in the collaborative training effort has been high. Of particular importance in this environment is orchestration of efforts among interested parties with similar goals in Peru, and integration of informatics skills into ongoing large-scale research projects in country.

Person-generated Data in Self-quantification. A Health Informatics Research Program.

PubMed

Gray, Kathleen; Martin-Sanchez, Fernando J; Lopez-Campos, Guillermo H; Almalki, Manal; Merolli, Mark

2017-01-09

The availability of internet-connected mobile, wearable and ambient consumer technologies, direct-to-consumer e-services and peer-to-peer social media sites far outstrips evidence about the efficiency, effectiveness and efficacy of using them in healthcare applications. The aim of this paper is to describe one approach to build a program of health informatics research, so as to generate rich and robust evidence about health data and information processing in self-quantification and associated healthcare and health outcomes. The paper summarises relevant health informatics research approaches in the literature and presents an example of developing a program of research in the Health and Biomedical Informatics Centre (HaBIC) at the University of Melbourne. The paper describes this program in terms of research infrastructure, conceptual models, research design, research reporting and knowledge sharing. The paper identifies key outcomes from integrative and multiple-angle approaches to investigating the management of information and data generated by use of this Centre's collection of wearable, mobiles and other devices in health self-monitoring experiments. These research results offer lessons for consumers, developers, clinical practitioners and biomedical and health informatics researchers. Health informatics is increasingly called upon to make sense of emerging self-quantification and other digital health phenomena that are well beyond the conventions of healthcare in which the field of informatics originated and consolidated. To make a substantial contribution to optimise the aims, processes and outcomes of health self-quantification needs further work at scale in multi-centre collaborations for this Centre and for health informatics researchers generally.

Search and Graph Database Technologies for Biomedical Semantic Indexing: Experimental Analysis.

PubMed

Segura Bedmar, Isabel; Martínez, Paloma; Carruana Martín, Adrián

2017-12-01

Biomedical semantic indexing is a very useful support tool for human curators in their efforts for indexing and cataloging the biomedical literature. The aim of this study was to describe a system to automatically assign Medical Subject Headings (MeSH) to biomedical articles from MEDLINE. Our approach relies on the assumption that similar documents should be classified by similar MeSH terms. Although previous work has already exploited the document similarity by using a k-nearest neighbors algorithm, we represent documents as document vectors by search engine indexing and then compute the similarity between documents using cosine similarity. Once the most similar documents for a given input document are retrieved, we rank their MeSH terms to choose the most suitable set for the input document. To do this, we define a scoring function that takes into account the frequency of the term into the set of retrieved documents and the similarity between the input document and each retrieved document. In addition, we implement guidelines proposed by human curators to annotate MEDLINE articles; in particular, the heuristic that says if 3 MeSH terms are proposed to classify an article and they share the same ancestor, they should be replaced by this ancestor. The representation of the MeSH thesaurus as a graph database allows us to employ graph search algorithms to quickly and easily capture hierarchical relationships such as the lowest common ancestor between terms. Our experiments show promising results with an F1 of 69% on the test dataset. To the best of our knowledge, this is the first work that combines search and graph database technologies for the task of biomedical semantic indexing. Due to its horizontal scalability, ElasticSearch becomes a real solution to index large collections of documents (such as the bibliographic database MEDLINE). Moreover, the use of graph search algorithms for accessing MeSH information could provide a support tool for cataloging MEDLINE abstracts in real time. ©Isabel Segura Bedmar, Paloma Martínez, Adrián Carruana Martín. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 01.12.2017.

Incorporating collaboratory concepts into informatics in support of translational interdisciplinary biomedical research

PubMed Central

Lee, E. Sally; McDonald, David W.; Anderson, Nicholas; Tarczy-Hornoch, Peter

2008-01-01

Due to its complex nature, modern biomedical research has become increasingly interdisciplinary and collaborative in nature. Although a necessity, interdisciplinary biomedical collaboration is difficult. There is, however, a growing body of literature on the study and fostering of collaboration in fields such as computer supported cooperative work (CSCW) and information science (IS). These studies of collaboration provide insight into how to potentially alleviate the difficulties of interdisciplinary collaborative research. We, therefore, undertook a cross cutting study of science and engineering collaboratories to identify emergent themes. We review many relevant collaboratory concepts: (a) general collaboratory concepts across many domains: communication, common workspace and coordination, and data sharing and management, (b) specific collaboratory concepts of particular biomedical relevance: data integration and analysis, security structure, metadata and data provenance, and interoperability and data standards, (c) environmental factors that support collaboratories: administrative and management structure, technical support, and available funding as critical environmental factors, and (d) future considerations for biomedical collaboration: appropriate training and long-term planning. In our opinion, the collaboratory concepts we discuss can guide planning and design of future collaborative infrastructure by biomedical informatics researchers to alleviate some of the difficulties of interdisciplinary biomedical collaboration. PMID:18706852

Toward More Successful Biomedical Informatics Education Programs and Ecosystems in the Arab World.

PubMed

Wageih, Mohamed A; Marcano-Cedeño, Alexis; Gómez, Enrique J; Mantas, John

2015-01-01

Biomedical & Health Informatics (BMHI) is relatively new in Arab States. However, several programs/ tracks are running, with high promises of expansion. Programs are evaluated by national authorities, not by a specialized body/association. This does not always mean that the program is of an international standard. One of the possible ways of ensuring the quality of these programs is to be evaluated by international agencies. The International Medical Informatics Association (IMIA) has the expertise in the evaluation BMHI education programs. Accredited programs staffs will have the opportunities for Internationalization and to be engaged with other top-notch organizations, which will have great impacts on the overall implementations of the BMHI in the Arab World. The goal of this document is to show to Arab Universities (pilot: Egypt) how to apply for IMIA Accreditation for their programs.

Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics.

PubMed

Roberts, Kirk; Boland, Mary Regina; Pruinelli, Lisiane; Dcruz, Jina; Berry, Andrew; Georgsson, Mattias; Hazen, Rebecca; Sarmiento, Raymond F; Backonja, Uba; Yu, Kun-Hsing; Jiang, Yun; Brennan, Patricia Flatley

2017-04-01

The field of biomedical informatics experienced a productive 2015 in terms of research. In order to highlight the accomplishments of that research, elicit trends, and identify shortcomings at a macro level, a 19-person team conducted an extensive review of the literature in clinical and consumer informatics. The result of this process included a year-in-review presentation at the American Medical Informatics Association Annual Symposium and a written report (see supplemental data). Key findings are detailed in the report and summarized here. This article organizes the clinical and consumer health informatics research from 2015 under 3 themes: the electronic health record (EHR), the learning health system (LHS), and consumer engagement. Key findings include the following: (1) There are significant advances in establishing policies for EHR feature implementation, but increased interoperability is necessary for these to gain traction. (2) Decision support systems improve practice behaviors, but evidence of their impact on clinical outcomes is still lacking. (3) Progress in natural language processing (NLP) suggests that we are approaching but have not yet achieved truly interactive NLP systems. (4) Prediction models are becoming more robust but remain hampered by the lack of interoperable clinical data records. (5) Consumers can and will use mobile applications for improved engagement, yet EHR integration remains elusive. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Towards to an Oncology Database (ONCOD) using a data warehousing approach

PubMed Central

Wang, Xiaoming; Liu, Lili; Fackenthal, James; Chang, Paul; Newstead, Gilliam; Chmura, Steven; Foster, Ian; Olopade, Olufunmilayo I

2012-01-01

While data warehousing approaches have been increasingly adopted in the biomedical informatics community for individualized data integration, effectively dealing with data integration, access, and application remains a challenging issue. In this report, focusing on ontology data, we describe how to use an established data warehouse system, named TRAM, to provide a data mart layer to address this issue. Our effort has resulted in a twofold achievement: 1) a model data mart tailored to facilitate oncology data integration and application (ONCOD), and 2) a flexible system architecture that has potential to be customized to support other data marts for various major medical fields. PMID:22779060

Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.

PubMed

Kibbe, Warren A; Arze, Cesar; Felix, Victor; Mitraka, Elvira; Bolton, Evan; Fu, Gang; Mungall, Christopher J; Binder, Janos X; Malone, James; Vasant, Drashtti; Parkinson, Helen; Schriml, Lynn M

2015-01-01

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years. These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protégé to curate DO in web ontology language. This will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Disease Ontology 2015 update: An expanded and updated database of human diseases for linking biomedical knowledge through disease data

DOE PAGES

Kibbe, Warren A.; Arze, Cesar; Felix, Victor; ...

2014-10-27

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years.more » These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protégé to curate DO in web ontology language. In conclusion, this will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning.« less

Disease Ontology 2015 update: An expanded and updated database of human diseases for linking biomedical knowledge through disease data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kibbe, Warren A.; Arze, Cesar; Felix, Victor

The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens of human disease. DO is a biomedical resource of standardized common and rare disease concepts with stable identifiers organized by disease etiology. The content of DO has had 192 revisions since 2012, including the addition of 760 terms. Thirty-two percent of all terms now include definitions. DO has expanded the number and diversity of research communities and community members by 50+ during the past two years.more » These community members actively submit term requests, coordinate biomedical resource disease representation and provide expert curation guidance. Since the DO 2012 NAR paper, there have been hundreds of term requests and a steady increase in the number of DO listserv members, twitter followers and DO website usage. DO is moving to a multi-editor model utilizing Protégé to curate DO in web ontology language. In conclusion, this will enable closer collaboration with the Human Phenotype Ontology, EBI's Ontology Working Group, Mouse Genome Informatics and the Monarch Initiative among others, and enhance DO's current asserted view and multiple inferred views through reasoning.« less

Biomedical Informatics on the Cloud: A Treasure Hunt for Advancing Cardiovascular Medicine.

PubMed

Ping, Peipei; Hermjakob, Henning; Polson, Jennifer S; Benos, Panagiotis V; Wang, Wei

2018-04-27

In the digital age of cardiovascular medicine, the rate of biomedical discovery can be greatly accelerated by the guidance and resources required to unearth potential collections of knowledge. A unified computational platform leverages metadata to not only provide direction but also empower researchers to mine a wealth of biomedical information and forge novel mechanistic insights. This review takes the opportunity to present an overview of the cloud-based computational environment, including the functional roles of metadata, the architecture schema of indexing and search, and the practical scenarios of machine learning-supported molecular signature extraction. By introducing several established resources and state-of-the-art workflows, we share with our readers a broadly defined informatics framework to phenotype cardiovascular health and disease. © 2018 American Heart Association, Inc.

IT Strategic Planning Workshops Develop Long-Term Goals | Poster

Cancer.gov

As part of NCI’s Research IT Strategic Planning efforts, a workshop was held on the NIH main campus in June. The main purpose of the workshop was to discuss ways to better integrate IT and informatics throughout NCI, and develop specific, high-level goals and related objectives that will drive the direction of IT and informatics support over the next five years. The initiative to integrate NCI’s IT and informatics is a collaboration between the Center for Biomedical Informatics and Information Technology (CBIIT), Office of Scientific Operations, Data Management Services, and the IT Operations Group.

Heterogeneous Biomedical Database Integration Using a Hybrid Strategy: A p53 Cantcer Research Database

PubMed Central

Bichutskiy, Vadim Y.; Colman, Richard; Brachmann, Rainer K.; Lathrop, Richard H.

2006-01-01

Complex problems in life science research give rise to multidisciplinary collaboration, and hence, to the need for heterogeneous database integration. The tumor suppressor p53 is mutated in close to 50% of human cancers, and a small drug-like molecule with the ability to restore native function to cancerous p53 mutants is a long-held medical goal of cancer treatment. The Cancer Research DataBase (CRDB) was designed in support of a project to find such small molecules. As a cancer informatics project, the CRDB involved small molecule data, computational docking results, functional assays, and protein structure data. As an example of the hybrid strategy for data integration, it combined the mediation and data warehousing approaches. This paper uses the CRDB to illustrate the hybrid strategy as a viable approach to heterogeneous data integration in biomedicine, and provides a design method for those considering similar systems. More efficient data sharing implies increased productivity, and, hopefully, improved chances of success in cancer research. (Code and database schemas are freely downloadable, http://www.igb.uci.edu/research/research.html.) PMID:19458771

A decade of experience in the development and implementation of tissue banking informatics tools for intra and inter-institutional translational research

PubMed Central

Amin, Waqas; Singh, Harpreet; Pople, Andre K.; Winters, Sharon; Dhir, Rajiv; Parwani, Anil V.; Becich, Michael J.

2010-01-01

Context: Tissue banking informatics deals with standardized annotation, collection and storage of biospecimens that can further be shared by researchers. Over the last decade, the Department of Biomedical Informatics (DBMI) at the University of Pittsburgh has developed various tissue banking informatics tools to expedite translational medicine research. In this review, we describe the technical approach and capabilities of these models. Design: Clinical annotation of biospecimens requires data retrieval from various clinical information systems and the de-identification of the data by an honest broker. Based upon these requirements, DBMI, with its collaborators, has developed both Oracle-based organ-specific data marts and a more generic, model-driven architecture for biorepositories. The organ-specific models are developed utilizing Oracle 9.2.0.1 server tools and software applications and the model-driven architecture is implemented in a J2EE framework. Result: The organ-specific biorepositories implemented by DBMI include the Cooperative Prostate Cancer Tissue Resource (http://www.cpctr.info/), Pennsylvania Cancer Alliance Bioinformatics Consortium (http://pcabc.upmc.edu/main.cfm), EDRN Colorectal and Pancreatic Neoplasm Database (http://edrn.nci.nih.gov/) and Specialized Programs of Research Excellence (SPORE) Head and Neck Neoplasm Database (http://spores.nci.nih.gov/current/hn/index.htm). The model-based architecture is represented by the National Mesothelioma Virtual Bank (http://mesotissue.org/). These biorepositories provide thousands of well annotated biospecimens for the researchers that are searchable through query interfaces available via the Internet. Conclusion: These systems, developed and supported by our institute, serve to form a common platform for cancer research to accelerate progress in clinical and translational research. In addition, they provide a tangible infrastructure and resource for exposing research resources and biospecimen services in collaboration with the clinical anatomic pathology laboratory information system (APLIS) and the cancer registry information systems. PMID:20922029

A decade of experience in the development and implementation of tissue banking informatics tools for intra and inter-institutional translational research.

PubMed

Amin, Waqas; Singh, Harpreet; Pople, Andre K; Winters, Sharon; Dhir, Rajiv; Parwani, Anil V; Becich, Michael J

2010-08-10

Tissue banking informatics deals with standardized annotation, collection and storage of biospecimens that can further be shared by researchers. Over the last decade, the Department of Biomedical Informatics (DBMI) at the University of Pittsburgh has developed various tissue banking informatics tools to expedite translational medicine research. In this review, we describe the technical approach and capabilities of these models. Clinical annotation of biospecimens requires data retrieval from various clinical information systems and the de-identification of the data by an honest broker. Based upon these requirements, DBMI, with its collaborators, has developed both Oracle-based organ-specific data marts and a more generic, model-driven architecture for biorepositories. The organ-specific models are developed utilizing Oracle 9.2.0.1 server tools and software applications and the model-driven architecture is implemented in a J2EE framework. The organ-specific biorepositories implemented by DBMI include the Cooperative Prostate Cancer Tissue Resource (http://www.cpctr.info/), Pennsylvania Cancer Alliance Bioinformatics Consortium (http://pcabc.upmc.edu/main.cfm), EDRN Colorectal and Pancreatic Neoplasm Database (http://edrn.nci.nih.gov/) and Specialized Programs of Research Excellence (SPORE) Head and Neck Neoplasm Database (http://spores.nci.nih.gov/current/hn/index.htm). The model-based architecture is represented by the National Mesothelioma Virtual Bank (http://mesotissue.org/). These biorepositories provide thousands of well annotated biospecimens for the researchers that are searchable through query interfaces available via the Internet. These systems, developed and supported by our institute, serve to form a common platform for cancer research to accelerate progress in clinical and translational research. In addition, they provide a tangible infrastructure and resource for exposing research resources and biospecimen services in collaboration with the clinical anatomic pathology laboratory information system (APLIS) and the cancer registry information systems.

ChemBank: a small-molecule screening and cheminformatics resource database.

PubMed

Seiler, Kathleen Petri; George, Gregory A; Happ, Mary Pat; Bodycombe, Nicole E; Carrinski, Hyman A; Norton, Stephanie; Brudz, Steve; Sullivan, John P; Muhlich, Jeremy; Serrano, Martin; Ferraiolo, Paul; Tolliday, Nicola J; Schreiber, Stuart L; Clemons, Paul A

2008-01-01

ChemBank (http://chembank.broad.harvard.edu/) is a public, web-based informatics environment developed through a collaboration between the Chemical Biology Program and Platform at the Broad Institute of Harvard and MIT. This knowledge environment includes freely available data derived from small molecules and small-molecule screens and resources for studying these data. ChemBank is unique among small-molecule databases in its dedication to the storage of raw screening data, its rigorous definition of screening experiments in terms of statistical hypothesis testing, and its metadata-based organization of screening experiments into projects involving collections of related assays. ChemBank stores an increasingly varied set of measurements derived from cells and other biological assay systems treated with small molecules. Analysis tools are available and are continuously being developed that allow the relationships between small molecules, cell measurements, and cell states to be studied. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the Broad Institute by collaborators from the worldwide research community. The goal of ChemBank is to provide life scientists unfettered access to biomedically relevant data and tools heretofore available primarily in the private sector.

Visualizing the Structure of Medical Informatics Using Term Co-Occurrence Analysis: II. INSPEC Perspective.

ERIC Educational Resources Information Center

Morris, Theodore

2001-01-01

Term co-occurrence analysis of INSPEC classification codes and thesaurus terms used to index Medical Informatics literature reveals an information science and technology perspective on the field, to accompany the biomedical perspective previously reported. This study continues the search for a better understanding of the structure of Medical…

Integrating Governance of Research Informatics and Health Care IT Across an Enterprise: Experiences from the Trenches.

PubMed

Embi, Peter J; Tachinardi, Umberto; Lussier, Yves; Starren, Justin; Silverstein, Jonathan

2013-01-01

Advances in health information technology and biomedical informatics have laid the groundwork for significant improvements in healthcare and biomedical research. For instance, Electronic Health Records can help improve the delivery of evidence-based care, enhance quality, and contribute to discoveries and evidence generation. Despite this promise, there are many challenges to achieving the vision and missions of our healthcare and research enterprises. Given the challenges inherent in doing so, institutions are increasingly moving to establish dedicated leadership and governance models charged with designing, deploying and leveraging various information resources to advance research and advanced care activities at AHCs. Some institutions have even created a new leadership position to oversee such activities, such as the Chief Research Information Officer. This panel will include research informatics leaders discussing their experiences from the proverbial trenches as they work to operationalize such cross-mission governance models. Panelists will start by providing an overview their respective positions and environments, discuss their experiences, and share lessons learned through their work at the intersection of clinical and translational research informatics and Health IT.

Health information technology and the medical school curriculum.

PubMed

Triola, Marc M; Friedman, Erica; Cimino, Christopher; Geyer, Enid M; Wiederhorn, Jo; Mainiero, Crystal

2010-12-01

Medical schools must teach core biomedical informatics competencies that address health information technology (HIT), including explaining electronic medical record systems and computerized provider order entry systems and their role in patient safety; describing the research uses and limitations of a clinical data warehouse; understanding the concepts and importance of information system interoperability; explaining the difference between biomedical informatics and HIT; and explaining the ways clinical information systems can fail. Barriers to including these topics in the curricula include lack of teachers; the perception that informatics competencies are not applicable during preclinical courses and there is no place in the clerkships to teach them; and the legal and policy issues that conflict with students' need to develop skills. However, curricular reform efforts are creating opportunities to teach these topics with new emphasis on patient safety, team-based medical practice, and evidence-based care. Overarching HIT competencies empower our students to be lifelong technology learners.

It's Just (Academic) Business: A Use Case in Improving Informatics Operations with Business Intelligence.

PubMed

McIntosh, Leslie D; Zabarovskaya, Connie; Uhlmansiek, Mary

2015-01-01

Academic biomedical informatics cores are beholden to funding agencies, institutional administration, collaborating researchers, and external agencies for ongoing funding and support. Services provided and translational research outcomes are increasingly important to monitor, report and analyze, to demonstrate value provided to the organization and the greater scientific community. Thus, informatics operations are also business operations. As such, adopting business intelligence practices offers an opportunity to improve the efficiency of evaluation efforts while fulfilling reporting requirements. Organizing informatics development documentation, service requests, and work performed with adaptable tools have greatly facilitated these and related business activities within our informatics center. Through the identification and measurement of key performance indicators, informatics objectives and results are now quickly and nimbly assessed using dashboards. Acceptance of the informatics operation as a business venture and the adoption of business intelligence strategies has allowed for data-driven decision making, faster corrective action, and greater transparency for interested stakeholders.

Eleven quick tips for architecting biomedical informatics workflows with cloud computing.

PubMed

Cole, Brian S; Moore, Jason H

2018-03-01

Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world's largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction.

Eleven quick tips for architecting biomedical informatics workflows with cloud computing

PubMed Central

Moore, Jason H.

2018-01-01

Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world’s largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction. PMID:29596416

Visibility of medical informatics regarding bibliometric indices and databases

PubMed Central

2011-01-01

Background The quantitative study of the publication output (bibliometrics) deeply influences how scientific work is perceived (bibliometric visibility). Recently, new bibliometric indices and databases have been established, which may change the visibility of disciplines, institutions and individuals. This study examines the effects of the new indices on the visibility of Medical Informatics. Methods By objective criteria, three sets of journals are chosen, two representing Medical Informatics and a third addressing Internal Medicine as a benchmark. The availability of index data (index coverage) and the aggregate scores of these corpora are compared for journal-related (Journal impact factor, Eigenfactor metrics, SCImago journal rank) and author-related indices (Hirsch-index, Egghes G-index). Correlation analysis compares the dependence of author-related indices. Results The bibliometric visibility depended on the research focus and the citation database: Scopus covers more journals relevant for Medical Informatics than ISI/Thomson Reuters. Journals focused on Medical Informatics' methodology were negatively affected by the Eigenfactor metrics, while the visibility profited from an interdisciplinary research focus. The correlation between Hirsch-indices computed on citation databases and the Internet was strong. Conclusions The visibility of smaller technology-oriented disciplines like Medical Informatics is changed by the new bibliometric indices and databases possibly leading to suitably changed publication strategies. Freely accessible author-related indices enable an easy and adequate individual assessment. PMID:21496230

Mouse Genome Database: From sequence to phenotypes and disease models

PubMed Central

Richardson, Joel E.; Kadin, James A.; Smith, Cynthia L.; Blake, Judith A.; Bult, Carol J.

2015-01-01

Summary The Mouse Genome Database (MGD, www.informatics.jax.org) is the international scientific database for genetic, genomic, and biological data on the laboratory mouse to support the research requirements of the biomedical community. To accomplish this goal, MGD provides broad data coverage, serves as the authoritative standard for mouse nomenclature for genes, mutants, and strains, and curates and integrates many types of data from literature and electronic sources. Among the key data sets MGD supports are: the complete catalog of mouse genes and genome features, comparative homology data for mouse and vertebrate genes, the authoritative set of Gene Ontology (GO) annotations for mouse gene functions, a comprehensive catalog of mouse mutations and their phenotypes, and a curated compendium of mouse models of human diseases. Here, we describe the data acquisition process, specifics about MGD's key data areas, methods to access and query MGD data, and outreach and user help facilities. genesis 53:458–473, 2015. © 2015 The Authors. Genesis Published by Wiley Periodicals, Inc. PMID:26150326

Recommendations of the International Medical Informatics Association (IMIA) on Education in Biomedical and Health Informatics. First Revision.

PubMed

Mantas, John; Ammenwerth, Elske; Demiris, George; Hasman, Arie; Haux, Reinhold; Hersh, William; Hovenga, Evelyn; Lun, K C; Marin, Heimar; Martin-Sanchez, Fernando; Wright, Graham

2010-01-07

Objective: The International Medical Informatics Association (IMIA) agreed on revising the existing international recommendations in health informatics/medical informatics education. These should help to establish courses, course tracks or even complete programs in this field, to further develop existing educational activities in the various nations and to support international initiatives concerning education in biomedical and health informatics (BMHI), particularly international activities in educating BMHI specialists and the sharing of courseware. Method: An IMIA task force, nominated in 2006, worked on updating the recommendations' first version. These updates have been broadly discussed and refined by members of IMIA's National Member Societies, IMIA's Academic Institutional Members and by members of IMIA's Working Group on Health and Medical Informatics Education. Results and Conclusions: The IMIA recommendations center on educational needs for health care professionals to acquire knowledge and skills in information processing and information and communication technology. The educational needs are described as a three-dimensional framework. The dimensions are: 1) professionals in health care (e.g. physicians, nurses, BMHI professionals), 2) type of specialization in BMHI (IT users, BMHI specialists), and 3) stage of career progression (bachelor, master, doctorate). Learning outcomes are defined in terms of knowledge and practical skills for health care professionals in their role a) as IT user and b) as BMHI specialist. Recommendations are given for courses/course tracks in BMHI as part of educational programs in medicine, nursing, health care management, dentistry, pharmacy, public health, health record administration, and informatics/computer science as well as for dedicated programs in BMHI (with bachelor, master or doctor degree). To support education in BMHI, IMIA offers to award a certificate for high-quality BMHI education. It supports information exchange on programs and courses in BMHI through its Working Group on Health and Medical Informatics Education.

Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2)

PubMed Central

Weber, Griffin; Mendis, Michael; Gainer, Vivian; Chueh, Henry C; Churchill, Susanne; Kohane, Isaac

2010-01-01

Informatics for Integrating Biology and the Bedside (i2b2) is one of seven projects sponsored by the NIH Roadmap National Centers for Biomedical Computing (http://www.ncbcs.org). Its mission is to provide clinical investigators with the tools necessary to integrate medical record and clinical research data in the genomics age, a software suite to construct and integrate the modern clinical research chart. i2b2 software may be used by an enterprise's research community to find sets of interesting patients from electronic patient medical record data, while preserving patient privacy through a query tool interface. Project-specific mini-databases (“data marts”) can be created from these sets to make highly detailed data available on these specific patients to the investigators on the i2b2 platform, as reviewed and restricted by the Institutional Review Board. The current version of this software has been released into the public domain and is available at the URL: http://www.i2b2.org/software. PMID:20190053

Data Mining Algorithms for Classification of Complex Biomedical Data

ERIC Educational Resources Information Center

Lan, Liang

2012-01-01

In my dissertation, I will present my research which contributes to solve the following three open problems from biomedical informatics: (1) Multi-task approaches for microarray classification; (2) Multi-label classification of gene and protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray…

75 FR 42102 - National Library of Medicine; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-20

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health National Library of Medicine....S.C. App), notice is hereby given of a meeting of the Biomedical Library and Informatics Review... constitute a clearly unwarranted invasion of personal privacy. Name of Committee: Biomedical Library and...

75 FR 80512 - National Library of Medicine; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-22

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health National Library of Medicine....S.C. App), notice is hereby given of a meeting of the Biomedical Library and Informatics Review... constitute a clearly unwarranted invasion of personal privacy. Name of Committee: Biomedical Library and...

76 FR 14037 - National Library of Medicine; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-15

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health National Library of Medicine....S.C. App), notice is hereby given of a meeting of the Biomedical Library and Informatics Review... constitute a clearly unwarranted invasion of personal privacy. Name of Committee: Biomedical Library and...

Big biomedical data as the key resource for discovery science.

PubMed

Toga, Arthur W; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W; Price, Nathan D; Glusman, Gustavo; Heavner, Benjamin D; Dinov, Ivo D; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

2015-11-01

Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Leveraging the national cyberinfrastructure for biomedical research.

PubMed

LeDuc, Richard; Vaughn, Matthew; Fonner, John M; Sullivan, Michael; Williams, James G; Blood, Philip D; Taylor, James; Barnett, William

2014-01-01

In the USA, the national cyberinfrastructure refers to a system of research supercomputer and other IT facilities and the high speed networks that connect them. These resources have been heavily leveraged by scientists in disciplines such as high energy physics, astronomy, and climatology, but until recently they have been little used by biomedical researchers. We suggest that many of the 'Big Data' challenges facing the medical informatics community can be efficiently handled using national-scale cyberinfrastructure. Resources such as the Extreme Science and Discovery Environment, the Open Science Grid, and Internet2 provide economical and proven infrastructures for Big Data challenges, but these resources can be difficult to approach. Specialized web portals, support centers, and virtual organizations can be constructed on these resources to meet defined computational challenges, specifically for genomics. We provide examples of how this has been done in basic biology as an illustration for the biomedical informatics community.

Leveraging the national cyberinfrastructure for biomedical research

PubMed Central

LeDuc, Richard; Vaughn, Matthew; Fonner, John M; Sullivan, Michael; Williams, James G; Blood, Philip D; Taylor, James; Barnett, William

2014-01-01

In the USA, the national cyberinfrastructure refers to a system of research supercomputer and other IT facilities and the high speed networks that connect them. These resources have been heavily leveraged by scientists in disciplines such as high energy physics, astronomy, and climatology, but until recently they have been little used by biomedical researchers. We suggest that many of the ‘Big Data’ challenges facing the medical informatics community can be efficiently handled using national-scale cyberinfrastructure. Resources such as the Extreme Science and Discovery Environment, the Open Science Grid, and Internet2 provide economical and proven infrastructures for Big Data challenges, but these resources can be difficult to approach. Specialized web portals, support centers, and virtual organizations can be constructed on these resources to meet defined computational challenges, specifically for genomics. We provide examples of how this has been done in basic biology as an illustration for the biomedical informatics community. PMID:23964072

Women's Self-Identified Sources of Student Support in a Master's-Level Health Informatics Database Course

ERIC Educational Resources Information Center

Feinberg, Daniel A.

2017-01-01

This study examined the supports that female students sought out and found of value in an online database design course in a health informatics master's program. A target outcome was to help inform the practice of faculty and administrators in similar programs. Health informatics is a growing field that has faced shortages of qualified workers who…

The Jubilee of Medical Informatics in Bosnia and Herzegovina - 20 Years Anniversary

PubMed Central

Masic, Izet

2009-01-01

CONFLICT OF INTEREST: NONE DECLARED Last two years, the health informatics profession celebrated five jubilees in Bosnia and Herzegovina: thirty years from the introduction of the first automatic manipulation of data, twenty years from the establishment of Society for Medical Informatics BiH, fifteen years from the establishment of the Scientific and Professional Journal of the Society for Medical Informatics of Bosnia and Herzegovina „Acta Informatica Medica“, fifteen years on from the establishment of the first Cathedra for Medical Informatics on Biomedical Faculties in Bosnia and Herzegovina and five years on from the introduction of the method of “Distance learning” in medical curriculum. The author of this article are eager to mark the importance of the above mentioned Anniversaries in the development of Health informatics in Bosnia and Herzegovina and have attempted, very briefly, to present the most significant events and persons with essential roles throughout this period. PMID:24133382

The jubilee of medical informatics in bosnia and herzegovina - 20 years anniversary.

PubMed

Masic, Izet

2009-01-01

NONE DECLARED LAST TWO YEARS, THE HEALTH INFORMATICS PROFESSION CELEBRATED FIVE JUBILEES IN BOSNIA AND HERZEGOVINA: thirty years from the introduction of the first automatic manipulation of data, twenty years from the establishment of Society for Medical Informatics BiH, fifteen years from the establishment of the Scientific and Professional Journal of the Society for Medical Informatics of Bosnia and Herzegovina "Acta Informatica Medica", fifteen years on from the establishment of the first Cathedra for Medical Informatics on Biomedical Faculties in Bosnia and Herzegovina and five years on from the introduction of the method of "Distance learning" in medical curriculum. The author of this article are eager to mark the importance of the above mentioned Anniversaries in the development of Health informatics in Bosnia and Herzegovina and have attempted, very briefly, to present the most significant events and persons with essential roles throughout this period.

Medical informatics in medical research - the Severe Malaria in African Children (SMAC) Network's experience.

PubMed

Olola, C H O; Missinou, M A; Issifou, S; Anane-Sarpong, E; Abubakar, I; Gandi, J N; Chagomerana, M; Pinder, M; Agbenyega, T; Kremsner, P G; Newton, C R J C; Wypij, D; Taylor, T E

2006-01-01

Computers are widely used for data management in clinical trials in the developed countries, unlike in developing countries. Dependable systems are vital for data management, and medical decision making in clinical research. Monitoring and evaluation of data management is critical. In this paper we describe database structures and procedures of systems used to implement, coordinate, and sustain data management in Africa. We outline major lessons, challenges and successes achieved, and recommendations to improve medical informatics application in biomedical research in sub-Saharan Africa. A consortium of experienced research units at five sites in Africa in studying children with disease formed a new clinical trials network, Severe Malaria in African Children. In December 2000, the network introduced an observational study involving these hospital-based sites. After prototyping, relational database management systems were implemented for data entry and verification, data submission and quality assurance monitoring. Between 2000 and 2005, 25,858 patients were enrolled. Failure to meet data submission deadline and data entry errors correlated positively (correlation coefficient, r = 0.82), with more errors occurring when data was submitted late. Data submission lateness correlated inversely with hospital admissions (r = -0.62). Developing and sustaining dependable DBMS, ongoing modifications to optimize data management is crucial for clinical studies. Monitoring and communication systems are vital in multi-center networks for good data management. Data timeliness is associated with data quality and hospital admissions.

A Roadmap for caGrid, an Enterprise Grid Architecture for Biomedical Research

PubMed Central

Saltz, Joel; Hastings, Shannon; Langella, Stephen; Oster, Scott; Kurc, Tahsin; Payne, Philip; Ferreira, Renato; Plale, Beth; Goble, Carole; Ervin, David; Sharma, Ashish; Pan, Tony; Permar, Justin; Brezany, Peter; Siebenlist, Frank; Madduri, Ravi; Foster, Ian; Shanbhag, Krishnakant; Mead, Charlie; Hong, Neil Chue

2012-01-01

caGrid is a middleware system which combines the Grid computing, the service oriented architecture, and the model driven architecture paradigms to support development of interoperable data and analytical resources and federation of such resources in a Grid environment. The functionality provided by caGrid is an essential and integral component of the cancer Biomedical Informatics Grid (caBIG™) program. This program is established by the National Cancer Institute as a nationwide effort to develop enabling informatics technologies for collaborative, multi-institutional biomedical research with the overarching goal of accelerating translational cancer research. Although the main application domain for caGrid is cancer research, the infrastructure provides a generic framework that can be employed in other biomedical research and healthcare domains. The development of caGrid is an ongoing effort, adding new functionality and improvements based on feedback and use cases from the community. This paper provides an overview of potential future architecture and tooling directions and areas of improvement for caGrid and caGrid-like systems. This summary is based on discussions at a roadmap workshop held in February with participants from biomedical research, Grid computing, and high performance computing communities. PMID:18560123

A roadmap for caGrid, an enterprise Grid architecture for biomedical research.

PubMed

Saltz, Joel; Hastings, Shannon; Langella, Stephen; Oster, Scott; Kurc, Tahsin; Payne, Philip; Ferreira, Renato; Plale, Beth; Goble, Carole; Ervin, David; Sharma, Ashish; Pan, Tony; Permar, Justin; Brezany, Peter; Siebenlist, Frank; Madduri, Ravi; Foster, Ian; Shanbhag, Krishnakant; Mead, Charlie; Chue Hong, Neil

2008-01-01

caGrid is a middleware system which combines the Grid computing, the service oriented architecture, and the model driven architecture paradigms to support development of interoperable data and analytical resources and federation of such resources in a Grid environment. The functionality provided by caGrid is an essential and integral component of the cancer Biomedical Informatics Grid (caBIG) program. This program is established by the National Cancer Institute as a nationwide effort to develop enabling informatics technologies for collaborative, multi-institutional biomedical research with the overarching goal of accelerating translational cancer research. Although the main application domain for caGrid is cancer research, the infrastructure provides a generic framework that can be employed in other biomedical research and healthcare domains. The development of caGrid is an ongoing effort, adding new functionality and improvements based on feedback and use cases from the community. This paper provides an overview of potential future architecture and tooling directions and areas of improvement for caGrid and caGrid-like systems. This summary is based on discussions at a roadmap workshop held in February with participants from biomedical research, Grid computing, and high performance computing communities.

It’s Just (Academic) Business: A Use Case in Improving Informatics Operations with Business Intelligence

PubMed Central

McIntosh, Leslie D.; Zabarovskaya, Connie; Uhlmansiek, Mary

2015-01-01

Academic biomedical informatics cores are beholden to funding agencies, institutional administration, collaborating researchers, and external agencies for ongoing funding and support. Services provided and translational research outcomes are increasingly important to monitor, report and analyze, to demonstrate value provided to the organization and the greater scientific community. Thus, informatics operations are also business operations. As such, adopting business intelligence practices offers an opportunity to improve the efficiency of evaluation efforts while fulfilling reporting requirements. Organizing informatics development documentation, service requests, and work performed with adaptable tools have greatly facilitated these and related business activities within our informatics center. Through the identification and measurement of key performance indicators, informatics objectives and results are now quickly and nimbly assessed using dashboards. Acceptance of the informatics operation as a business venture and the adoption of business intelligence strategies has allowed for data-driven decision making, faster corrective action, and greater transparency for interested stakeholders. PMID:26306252

Informatics in radiology: An open-source and open-access cancer biomedical informatics grid annotation and image markup template builder.

PubMed

Mongkolwat, Pattanasak; Channin, David S; Kleper, Vladimir; Rubin, Daniel L

2012-01-01

In a routine clinical environment or clinical trial, a case report form or structured reporting template can be used to quickly generate uniform and consistent reports. Annotation and image markup (AIM), a project supported by the National Cancer Institute's cancer biomedical informatics grid, can be used to collect information for a case report form or structured reporting template. AIM is designed to store, in a single information source, (a) the description of pixel data with use of markups or graphical drawings placed on the image, (b) calculation results (which may or may not be directly related to the markups), and (c) supplemental information. To facilitate the creation of AIM annotations with data entry templates, an AIM template schema and an open-source template creation application were developed to assist clinicians, image researchers, and designers of clinical trials to quickly create a set of data collection items, thereby ultimately making image information more readily accessible.

Informatics in Radiology: An Open-Source and Open-Access Cancer Biomedical Informatics Grid Annotation and Image Markup Template Builder

PubMed Central

Channin, David S.; Rubin, Vladimir Kleper Daniel L.

2012-01-01

In a routine clinical environment or clinical trial, a case report form or structured reporting template can be used to quickly generate uniform and consistent reports. Annotation and Image Markup (AIM), a project supported by the National Cancer Institute’s cancer Biomedical Informatics Grid, can be used to collect information for a case report form or structured reporting template. AIM is designed to store, in a single information source, (a) the description of pixel data with use of markups or graphical drawings placed on the image, (b) calculation results (which may or may not be directly related to the markups), and (c) supplemental information. To facilitate the creation of AIM annotations with data entry templates, an AIM template schema and an open-source template creation application were developed to assist clinicians, image researchers, and designers of clinical trials to quickly create a set of data collection items, thereby ultimately making image information more readily accessible. © RSNA, 2012 PMID:22556315

Biomedical and health informatics education and research at the Information Technology Institute in Egypt.

PubMed

Hussein, R; Khalifa, A

2011-01-01

During the last decade, Egypt has experienced a revolution in the field of Information and Communication Technology (ICT) that has had a corresponding impact on the field of healthcare. Since 1993, the Information Technology Institute (ITI) has been leading the development of the Information Technology (IT) professional training and education in Egypt to produce top quality IT professionals who are considered now the backbone of the IT revolution in Egypt. For the past five years, ITI has been adopting the objective of building high caliber health professionals who can effectively serve the ever-growing information society. Academic links have been established with internationally renowned universities, e.g., Oregon Health and Science University (OHSU) in US, University of Leipzig in Germany, in addition those with the Egyptian Fellowship Board in order to enrich ITI Medical Informatics Education and Research. The ITI Biomedical and Health Informatics (BMHI) education and training programs target fresh graduates as well as life-long learners. Therefore, the program's learning objectives are framed within the context of the four specialization tracks: Healthcare Management (HCM), Biomedical Informatics Research (BMIR), Bioinformatics Professional (BIP), and Healthcare Professional (HCP). The ITI BMHI research projects tackle a wide-range of current challenges in this field, such as knowledge management in healthcare, providing tele-consultation services for diagnosis and treatment of infectious diseases for underserved regions in Egypt, and exploring the cultural and educational aspects of Nanoinformatics. Since 2006, ITI has been positively contributing to develop the discipline of BMHI in Egypt in order to support improved healthcare services.

Research Strategies for Biomedical and Health Informatics. Some Thought-provoking and Critical Proposals to Encourage Scientific Debate on the Nature of Good Research in Medical Informatics.

PubMed

Haux, Reinhold; Kulikowski, Casimir A; Bakken, Suzanne; de Lusignan, Simon; Kimura, Michio; Koch, Sabine; Mantas, John; Maojo, Victor; Marschollek, Michael; Martin-Sanchez, Fernando; Moen, Anne; Park, Hyeoun-Ae; Sarkar, Indra N; Leong, Tze Yun; McCray, Alexa T

2017-01-25

Medical informatics, or biomedical and health informatics (BMHI), has become an established scientific discipline. In all such disciplines there is a certain inertia to persist in focusing on well-established research areas and to hold on to well-known research methodologies rather than adopting new ones, which may be more appropriate. To search for answers to the following questions: What are research fields in informatics, which are not being currently adequately addressed, and which methodological approaches might be insufficiently used? Do we know about reasons? What could be consequences of change for research and for education? Outstanding informatics scientists were invited to three panel sessions on this topic in leading international conferences (MIE 2015, Medinfo 2015, HEC 2016) in order to get their answers to these questions. A variety of themes emerged in the set of answers provided by the panellists. Some panellists took the theoretical foundations of the field for granted, while several questioned whether the field was actually grounded in a strong theoretical foundation. Panellists proposed a range of suggestions for new or improved approaches, methodologies, and techniques to enhance the BMHI research agenda. The field of BMHI is on the one hand maturing as an academic community and intellectual endeavour. On the other hand vendor-supplied solutions may be too readily and uncritically accepted in health care practice. There is a high chance that BMHI will continue to flourish as an important discipline; its innovative interventions might then reach the original objectives of advancing science and improving health care outcomes.

Interdisciplinary innovations in biomedical and health informatics graduate education.

PubMed

Demiris, G

2007-01-01

Biomedical and health informatics (BHI) is a rapidly growing domain that relies on the active collaboration with diverse disciplines and professions. Educational initiatives in BHI need to prepare students with skills and competencies that will allow them to function within and even facilitate interdisciplinary teams (IDT). This paper describes an interdisciplinary educational approach introduced into a BHI graduate curriculum that aims to prepare informatics researchers to lead IDT research. A case study of the "gerontechnology" research track is presented which highlights how the curriculum fosters collaboration with and understanding of the disciplines of Nursing, Engineering, Computer Science, and Health Administration. Gerontechnology is a new interdisciplinary field that focuses on the use of technology to support aging. Its aim is to explore innovative ways to use information technology and develop systems that support independency and increase quality of life for senior citizens. As a result of a large research group that explores "smart home" technologies and the use of information technology, we integrated this new domain into the curriculum providing a platform for computer scientists, engineers, nurses and physicians to explore challenges and opportunities with our informatics students and faculty. The interdisciplinary educational model provides an opportunity for health informatics students to acquire the skills for communication and collaboration with other disciplines. Numerous graduate and postgraduate students have already participated in this initiative. The evaluation model of this approach is presented. Interdisciplinary educational models are required for health informatics graduate education. Such models need to be innovative and reflect the needs and trends in the domains of health care and information technology.

A curricula-based comparison of biomedical and health informatics programs in the USA

PubMed Central

Hemminger, Bradley M

2011-01-01

Objective The field of Biomedical and Health Informatics (BMHI) continues to define itself, and there are many educational programs offering ‘informatics’ degrees with varied foci. The goal of this study was to develop a scheme for systematic comparison of programs across the entire BMHI spectrum and to identify commonalities among informatics curricula. Design Guided by several published competency sets, a grounded theory approach was used to develop a program/curricula categorization scheme based on the descriptions of 636 courses offered by 73 public health, nursing, health, medical, and bioinformatics programs in the USA. The scheme was then used to compare the programs in the aforementioned five informatics disciplines. Results The authors developed a Course-Based Informatics Program Categorization (CBIPC) scheme that can be used both to classify coursework for any BMHI educational program and to compare programs from the same or related disciplines. The application of CBIPC scheme to the analysis of public health, nursing, health, medical, and bioinformatics programs reveals distinct intradisciplinary curricular patterns and a common core of courses across the entire BMHI education domain. Limitations The study is based on descriptions of courses from the university's webpages. Thus, it is limited to sampling courses at one moment in time, and classification for the coding scheme is based primarily on course titles and course descriptions. Conclusion The CBIPC scheme combines empirical data about educational curricula from diverse informatics programs and several published competency sets. It also provides a foundation for discussion of BMHI education as a whole and can help define subdisciplinary competencies. PMID:21292707

78 FR 40487 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-05

... Committee: Center for Scientific Review Special Emphasis Panel; Biomedical Technology Research Center: A Biomedical- Informatics Research Network for Big Data. Date: July 30-August 1, 2013. Time: 6:00 p.m. to 1:00... Scientific Review Special Emphasis Panel; Gene Therapy Member Conflicts. Date: July 30, 2013. Time: 3:00 p.m...

INFOBIOMED: European Network of Excellence on Biomedical Informatics to support individualised healthcare.

PubMed

Maojo, Victor; de la Calle, Guillermo; Martín-Sánchez, Fernando; Díaz, Carlos; Sanz, Ferran

2005-01-01

INFOBIOMED is an European Network of Excellence (NoE) funded by the Information Society Directorate-General of the European Commission (EC). A consortium of European organizations from ten different countries is involved within the network. Four pilots, all related to linking clinical and genomic information, are being carried out. From an informatics perspective, various challenges, related to data integration and mining, are included.

Medical informatics as a market for IS/IT.

PubMed Central

Morris, Theodore Allan

2002-01-01

Medical informatics is "the application of information science and information technology to the theoretical and practical problems of biomedical research, clinical practice, and medical education." A key difference between the two streams lies in their perspectives of "What Is Important in MI to Me?" MI may be seen as the marketplace where biomedicine consumes products and services provided by information science and information technology. PMID:12463882

An informatics research agenda to support precision medicine: seven key areas.

PubMed

Tenenbaum, Jessica D; Avillach, Paul; Benham-Hutchins, Marge; Breitenstein, Matthew K; Crowgey, Erin L; Hoffman, Mark A; Jiang, Xia; Madhavan, Subha; Mattison, John E; Nagarajan, Radhakrishnan; Ray, Bisakha; Shin, Dmitriy; Visweswaran, Shyam; Zhao, Zhongming; Freimuth, Robert R

2016-07-01

The recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to the forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue to evolve and datasets grow in magnitude, a strong computational infrastructure will be essential to realize PM's vision of improved healthcare derived from personal data. In addition, informatics research and innovation affords a tremendous opportunity to drive the science underlying PM. The informatics community must lead the development of technologies and methodologies that will increase the discovery and application of biomedical knowledge through close collaboration between researchers, clinicians, and patients. This perspective highlights seven key areas that are in need of further informatics research and innovation to support the realization of PM. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Closing the loops in biomedical informatics from theory to daily practice.

PubMed

Gaudinat, A

2009-01-01

This article presents the 2009 selection of the best papers in the special section dedicated to biomedical informatics and cybernetics. Synopsis of the articles selected for the IMIA yearbook 2009 Five papers from international peer reviewed journals where selected for this section. Most of the papers have a strong practical orientation in clinical care. And this selection gives a good overview of what is done with "closing loop" approach, particularly during the year 2008. While quite mature for some clinical applications such as mechanical ventilation, it remains a challenge where rules for the decision system could be difficult to identify due to the number of variables. More complex systems with greater Artificial Intelligence approaches will certainly be the next trend for closed-loop applications.

Sorrell v. IMS Health: issues and opportunities for informaticians

PubMed Central

Petersen, Carolyn; DeMuro, Paul; Goodman, Kenneth W; Kaplan, Bonnie

2013-01-01

In 2011, the US Supreme Court decided Sorrell v. IMS Health, Inc., a case that addressed the mining of large aggregated databases and the sale of prescriber data for marketing prescription drugs. The court struck down a Vermont law that required data mining companies to obtain permission from individual providers before selling prescription records that included identifiable physician prescription information to pharmaceutical companies for drug marketing. The decision was based on constitutional free speech protections rather than data sharing considerations. Sorrell illustrates challenges at the intersection of biomedical informatics, public health, constitutional liberties, and ethics. As states, courts, regulatory agencies, and federal bodies respond to Sorrell, informaticians’ expertise can contribute to more informed, ethical, and appropriate policies. PMID:23104048

The Biomarker Knowledge System Informatics Pilot Project Supplement To The Biomarker Development Laboratory at Moffitt (Bedlam) — EDRN Public Portal

Cancer.gov

The Biomarker Knowledge System Informatics Pilot Project goal will develop network interfaces among databases that contain information about existing clinical populations and biospecimens and data relating to those specimens that are important in biomarker assay validation. This protocol comprises one of two that will comprise the Moffitt participation in the Biomarker Knowledge System Informatics Pilot Project. THIS PROTOCOL (58) is the Sput-Epi Database.

Informatics Support for Basic Research in Biomedicine

PubMed Central

Rindflesch, Thomas C.; Blake, Catherine L.; Fiszman, Marcelo; Kilicoglu, Halil; Rosemblat, Graciela; Schneider, Jodi; Zeiss, Caroline J.

2017-01-01

Abstract Informatics methodologies exploit computer-assisted techniques to help biomedical researchers manage large amounts of information. In this paper, we focus on the biomedical research literature (MEDLINE). We first provide an overview of some text mining techniques that offer assistance in research by identifying biomedical entities (e.g., genes, substances, and diseases) and relations between them in text. We then discuss Semantic MEDLINE, an application that integrates PubMed document retrieval, concept and relation identification, and visualization, thus enabling a user to explore concepts and relations from within a set of retrieved citations. Semantic MEDLINE provides a roadmap through content and helps users discern patterns in large numbers of retrieved citations. We illustrate its use with an informatics method we call “discovery browsing,” which provides a principled way of navigating through selected aspects of some biomedical research area. The method supports an iterative process that accommodates learning and hypothesis formation in which a user is provided with high level connections before delving into details. As a use case, we examine current developments in basic research on mechanisms of Alzheimer’s disease. Out of the nearly 90 000 citations returned by the PubMed query “Alzheimer’s disease,” discovery browsing led us to 73 citations on sortilin and that disorder. We provide a synopsis of the basic research reported in 15 of these. There is wide-spread consensus among researchers working with a range of animal models and human cells that increased sortilin expression and decreased receptor expression are associated with amyloid beta and/or amyloid precursor protein. PMID:28838071

Accessing and integrating data and knowledge for biomedical research.

PubMed

Burgun, A; Bodenreider, O

2008-01-01

To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research.

Towards health informatics 3.0. Editorial.

PubMed

Kulikowski, Casimir A; Geissbuhler, Antoine

2011-01-01

To provide an editorial introduction to the 2011 IMIA Yearbook of Medical Informatics with an overview of its contents and contributors. A brief overview of the main theme, and an outline of the purposes, contents, format, and acknowledgment of contributions for the 2011 IMIA Yearbook. This 2011 issue of the IMIA Yearbook highlights important developments in the development of Web 3.0 capabilities that are increasing in Health Informatics, impacting the activities in research, education and practice in this interdisciplinary field. There has been steady progress towards introducing semantics into informatics systems through more sophisticated representations of knowledge in their underlying information. Health Informatics 3.0 capabilities are identified from the recent literature, illustrated by selected papers published during the past 12 months, and articles reported by IMIA Working Groups. Surveys of the main research sub-fields in biomedical informatics in the Yearbook provide an overview of progress and current challenges across the spectrum of the discipline, focusing on Web 3.0 challenges and opportunities.

A Short History of Medical Informatics in Bosnia and Herzegovina

PubMed Central

Masic, Izet

2014-01-01

The health informatics profession in Bosnia and Herzegovina has relatively long history. Thirty five years from the introduction of the first automatic manipulation of data, thirty years from the establishment of Society for Medical Informatics BiH, twenty years from the establishment of the Scientific journal “Acta Informatica Medica (Acta Inform Med”, indexed in PubMed, PubMed Central Scopus, Embase, etc.), twenty years on from the establishment of the first Cathedra for Medical Informatics on Biomedical Faculties in Bosnia and Herzegovina, ten years on from the introduction of the method of “Distance learning” in medical curriculum. The author of this article is eager to mark the importance of the above mentioned Anniversaries in the development of Health informatics in Bosnia and Herzegovina and have attempted, very briefly, to present the most significant events and persons with essential roles throughout this period. PMID:24648621

Bridging informatics and implementation science: evaluating a framework to assess electronic health record implementations in community settings.

PubMed

Richardson, Joshua E; Abramson, Erika L; Pfoh, Elizabeth R; Kaushal, Rainu

2012-01-01

Effective electronic health record (EHR) implementations in community settings are critical to promoting safe and reliable EHR use as well as mitigating provider dissatisfaction that often results. The implementation challenge is compounded given the scale and scope of EHR installations that are occurring and will continue to occur over the next five years. However, when compared to EHR evaluations relatively few biomedical informatics researchers have published on evaluating EHR implementations. Fewer still have evaluated EHR implementations in community settings. We report on the methods we used to achieve a novel application of an implementation science framework in informatics to qualitatively evaluate community-based EHR implementations. We briefly provide an overview of the implementation science framework, our methods for adapting it to informatics, the effects the framework had on our qualitative methods of inquiry and analysis, and discuss its potential value for informatics research.

A short history of medical informatics in bosnia and herzegovina.

PubMed

Masic, Izet

2014-02-01

The health informatics profession in Bosnia and Herzegovina has relatively long history. Thirty five years from the introduction of the first automatic manipulation of data, thirty years from the establishment of Society for Medical Informatics BiH, twenty years from the establishment of the Scientific journal "Acta Informatica Medica (Acta Inform Med", indexed in PubMed, PubMed Central Scopus, Embase, etc.), twenty years on from the establishment of the first Cathedra for Medical Informatics on Biomedical Faculties in Bosnia and Herzegovina, ten years on from the introduction of the method of "Distance learning" in medical curriculum. The author of this article is eager to mark the importance of the above mentioned Anniversaries in the development of Health informatics in Bosnia and Herzegovina and have attempted, very briefly, to present the most significant events and persons with essential roles throughout this period.

Informatics, evidence-based care, and research; implications for national policy: a report of an American Medical Informatics Association health policy conference.

PubMed

Bloomrosen, Meryl; Detmer, Don E

2010-01-01

There is an increased level of activity in the biomedical and health informatics world (e-prescribing, electronic health records, personal health records) that, in the near future, will yield a wealth of available data that we can exploit meaningfully to strengthen knowledge building and evidence creation, and ultimately improve clinical and preventive care. The American Medical Informatics Association (AMIA) 2008 Health Policy Conference was convened to focus and propel discussions about informatics-enabled evidence-based care, clinical research, and knowledge management. Conference participants explored the potential of informatics tools and technologies to improve the evidence base on which providers and patients can draw to diagnose and treat health problems. The paper presents a model of an evidence continuum that is dynamic, collaborative, and powered by health informatics technologies. The conference's findings are described, and recommendations on terminology harmonization, facilitation of the evidence continuum in a "wired" world, development and dissemination of clinical practice guidelines and other knowledge support strategies, and the role of diverse stakeholders in the generation and adoption of evidence are presented.

Ten years of international collaboration in biomedical informatics and beyond: the AMAUTA program in Peru

PubMed Central

Fuller, Sherrilynne; Garcia, Patricia J; Holmes, King K; Kimball, Ann Marie

2010-01-01

Well-trained people are urgently needed to tackle global health challenges through information and communication technologies. In this report, AMAUTA, a joint international collaborative training program between the Universidad Peruana Cayetano Heredia and the University of Washington, which has been training Peruvian health professionals in biomedical and health informatics since 1999, is described. Four short-term courses have been organized in Lima, offering training to more than 200 graduate-level students. Long-term training to masters or doctorate level has been undertaken by eight students at the University of Washington. A combination of short-term and long-term strategies was found to be effective for enhancing institutional research and training enterprise. The AMAUTA program promoted the development and institution of informatics research and training capacity in Peru, and has resulted in a group of trained people playing important roles at universities, non-government offices, and the Ministry of Health in Peru. At present, the hub is being extended into Latin American countries, promoting South-to-South collaborations. PMID:20595317

Trends in modeling Biomedical Complex Systems

PubMed Central

Milanesi, Luciano; Romano, Paolo; Castellani, Gastone; Remondini, Daniel; Liò, Petro

2009-01-01

In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented. PMID:19828068

An informatics research agenda to support precision medicine: seven key areas

PubMed Central

Avillach, Paul; Benham-Hutchins, Marge; Breitenstein, Matthew K; Crowgey, Erin L; Hoffman, Mark A; Jiang, Xia; Madhavan, Subha; Mattison, John E; Nagarajan, Radhakrishnan; Ray, Bisakha; Shin, Dmitriy; Visweswaran, Shyam; Zhao, Zhongming; Freimuth, Robert R

2016-01-01

The recent announcement of the Precision Medicine Initiative by President Obama has brought precision medicine (PM) to the forefront for healthcare providers, researchers, regulators, innovators, and funders alike. As technologies continue to evolve and datasets grow in magnitude, a strong computational infrastructure will be essential to realize PM’s vision of improved healthcare derived from personal data. In addition, informatics research and innovation affords a tremendous opportunity to drive the science underlying PM. The informatics community must lead the development of technologies and methodologies that will increase the discovery and application of biomedical knowledge through close collaboration between researchers, clinicians, and patients. This perspective highlights seven key areas that are in need of further informatics research and innovation to support the realization of PM. PMID:27107452

Women in biomedical engineering and health informatics and its impact on gender representation for accepted publications at IEEE EMBC 2007.

PubMed

McGregor, Carolyn; Smith, Kathleen P; Percival, Jennifer

2008-01-01

The study of women within the professions of Engineering and Computer Science has consistently been found to demonstrate women as a minority within these professions. However none of that previous work has assessed publication behaviours based on gender. This paper presents research findings on gender distribution of authors of accepted papers for the IEEE Engineering and Medicine Society annual conference for 2007 (EMBC '07) held in Lyon, France. This information is used to present a position statement of the current state of gender representation for conference publication within the domain of biomedical engineering and health informatics. Issues in data preparation resulting from the lack of inclusion of gender in information gathered from accepted authors are presented and discussed.

Biomedical informatics as support to individual healthcare in hereditary colon cancer: the Danish HNPCC system.

PubMed

Bernstein, Inge T; Lindorff-Larsen, Karen; Timshel, Susanne; Brandt, Carsten A; Dinesen, Birger; Fenger, Mogens; Gerdes, Anne-Marie; Iversen, Lene H; Madsen, Mogens R; Okkels, Henrik; Sunde, Lone; Rahr, Hans B; Wikman, Friedrick P; Rossing, Niels

2011-05-01

The Danish HNPCC register is a publically financed national database. The register gathers epidemiological and genomic data in HNPCC families to improve prognosis by screening and identifying family members at risk. Diagnostic data are generated throughout the country and collected over several decades. Until recently, paper-based reports were sent to the register and typed into the database. In the EC cofunded-INFOBIOMED network of excellence, the register was a model for electronic exchange of epidemiological and genomic data between diagnosing/treating departments and the central database. The aim of digitization was to optimize the organization of screening by facilitating combination of genotype-phenotype information, and to generate IT-tools sufficiently usable and generic to be implemented in other countries and for other oncogenetic diseases. The focus was on integration of heterogeneous data, elaboration, and dissemination of classification systems and development of communication standards. At the conclusion of the EU project in 2007 the system was implemented in 12 pilot departments. In the surgical departments this resulted in a 192% increase of reports to the database. Several gaps were identified: lack of standards for data to be exchanged, lack of local databases suitable for direct communication, reporting being time-consuming and dependent on interest and feedback. © 2011 Wiley-Liss, Inc.

Research Strategies for Biomedical and Health Informatics

PubMed Central

Kulikowski, Casimir A.; Bakken, Suzanne; de Lusignan, Simon; Kimura, Michio; Koch, Sabine; Mantas, John; Maojo, Victor; Marschollek, Michael; Martin-Sanchez, Fernando; Moen, Anne; Park, Hyeoun-Ae; Sarkar, Indra Neil; Leong, Tze Yun; McCray, Alexa T.

2017-01-01

Summary Background Medical informatics, or biomedical and health informatics (BMHI), has become an established scientific discipline. In all such disciplines there is a certain inertia to persist in focusing on well-established research areas and to hold on to well-known research methodologies rather than adopting new ones, which may be more appropriate. Objectives To search for answers to the following questions: What are research fields in informatics, which are not being currently adequately addressed, and which methodological approaches might be insufficiently used? Do we know about reasons? What could be consequences of change for research and for education? Methods Outstanding informatics scientists were invited to three panel sessions on this topic in leading international conferences (MIE 2015, Medinfo 2015, HEC 2016) in order to get their answers to these questions. Results A variety of themes emerged in the set of answers provided by the panellists. Some panellists took the theoretical foundations of the field for granted, while several questioned whether the field was actually grounded in a strong theoretical foundation. Panellists proposed a range of suggestions for new or improved approaches, methodologies, and techniques to enhance the BMHI research agenda. Conclusions The field of BMHI is on the one hand maturing as an academic community and intellectual endeavour. On the other hand vendor-supplied solutions may be too readily and uncritically accepted in health care practice. There is a high chance that BMHI will continue to flourish as an important discipline; its innovative interventions might then reach the original objectives of advancing science and improving health care outcomes. PMID:28119991

Accessing and Integrating Data and Knowledge for Biomedical Research

PubMed Central

Burgun, A.; Bodenreider, O.

2008-01-01

Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Methods Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. Conclusion As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research. PMID:18660883

Development of Multiscale Biological Image Data Analysis: Review of 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics, Santa Barbara, USA (BII06)

PubMed Central

Auer, Manfred; Peng, Hanchuan; Singh, Ambuj

2007-01-01

The 2006 International Workshop on Multiscale Biological Imaging, Data Mining and Informatics was held at Santa Barbara, on Sept 7–8, 2006. Based on the presentations at the workshop, we selected and compiled this collection of research articles related to novel algorithms and enabling techniques for bio- and biomedical image analysis, mining, visualization, and biology applications. PMID:17634090

Advancing the Framework: Use of Health Data—A Report of a Working Conference of the American Medical Informatics Association

PubMed Central

Bloomrosen, Meryl; Detmer, Don

2008-01-01

The fields of health informatics and biomedical research increasingly depend on the availability of aggregated health data. Yet, despite over fifteen years of policy work on health data issues, the United States (U.S.) lacks coherent policy to guide users striving to navigate the ethical, political, technical, and economic challenges associated with health data use. In 2007, building on more than a decade of previous work, the American Medical Informatics Association (AMIA) convened a panel of experts to stimulate discussion about and action on a national framework for health data use. This initiative is being carried out in the context of rapidly accelerating advances in the fields of health informatics and biomedical research, many of which are dependent on the availability of aggregated health data. Use of these data poses complex challenges that must be addressed by public policy. This paper highlights the results of the meeting, presents data stewardship as a key building block in the national framework, and outlines stewardship principles for the management of health information. The authors also introduce a taxonomy developed to focus definitions and terminology in the evolving field of health data applications. Finally, they identify areas for further policy analysis and recommend that public and private sector organizations elevate consideration of a national framework on the uses of health data to a top priority. PMID:18755988

An automatic method for retrieving and indexing catalogues of biomedical courses.

PubMed

Maojo, Victor; de la Calle, Guillermo; García-Remesal, Miguel; Bankauskaite, Vaida; Crespo, Jose

2008-11-06

Although there is wide information about Biomedical Informatics education and courses in different Websites, information is usually not exhaustive and difficult to update. We propose a new methodology based on information retrieval techniques for extracting, indexing and retrieving automatically information about educational offers. A web application has been developed to make available such information in an inventory of courses and educational offers.

78 FR 68462 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-14

... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel; Brain Injury and... Methodologies Integrated Review Group; Biomedical Computing and Health Informatics Study Section. Date: December...

Bioinformatics for transporter pharmacogenomics and systems biology: data integration and modeling with UML.

PubMed

Yan, Qing

2010-01-01

Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.

History of Romanian Medical Informatics: Learning from the Past to Reshape the Future.

PubMed

Mihalas, George I; Stoicu-Tivadar, Lacramioara

2018-04-22

 The paper presents a review of the history of medical informatics in Romania, starting from the pioneering works, relating the present, and foreseeing the future.  Major milestones of the development of this field have not been simply enumerated, but described within the specific socio-political frame, grasping the entire context over the last four decades in Romania. Two main perspectives have been traced: education and training in medical informatics and implementations in healthcare.  Four distinctive historical periods are identified and the major events of each period are described in a critical manner. The history of the Romanian Society of Medical Informatics is presented in a separate chapter. The last section is dedicated to the present state of the field in Romania.  The history of Romanian Medical Informatics spans many years and is rich in content. The Romanian Society of Medical Informatics is mainly the result of the efforts undertaken by an enthusiastic and sound professional community, trying to continue the tradition, to achieve new goals, and to work as an active member of the international biomedical/health informatics community. Georg Thieme Verlag KG Stuttgart.

The challenge of ubiquitous computing in health care: technology, concepts and solutions. Findings from the IMIA Yearbook of Medical Informatics 2005.

PubMed

Bott, O J; Ammenwerth, E; Brigl, B; Knaup, P; Lang, E; Pilgram, R; Pfeifer, B; Ruderich, F; Wolff, A C; Haux, R; Kulikowski, C

2005-01-01

To review recent research efforts in the field of ubiquitous computing in health care. To identify current research trends and further challenges for medical informatics. Analysis of the contents of the Yearbook on Medical Informatics 2005 of the International Medical Informatics Association (IMIA). The Yearbook of Medical Informatics 2005 includes 34 original papers selected from 22 peer-reviewed scientific journals related to several distinct research areas: health and clinical management, patient records, health information systems, medical signal processing and biomedical imaging, decision support, knowledge representation and management, education and consumer informatics as well as bioinformatics. A special section on ubiquitous health care systems is devoted to recent developments in the application of ubiquitous computing in health care. Besides additional synoptical reviews of each of the sections the Yearbook includes invited reviews concerning E-Health strategies, primary care informatics and wearable healthcare. Several publications demonstrate the potential of ubiquitous computing to enhance effectiveness of health services delivery and organization. But ubiquitous computing is also a societal challenge, caused by the surrounding but unobtrusive character of this technology. Contributions from nearly all of the established sub-disciplines of medical informatics are demanded to turn the visions of this promising new research field into reality.

Preface - Access to Knowledge Revisited

PubMed Central

Humphreys, Betsy L.

2016-01-01

Summary Objective To review and update the Preface to the 1998 Yearbook of Medical Informatics, which had as its Special Topic “Health Informatics and the Internet”. Method Assessment of the accuracy of predictions made in 1998 and consideration of key developments in informatics since that time. Results Predictions made in 1998 were generally accurate regarding reduced dependence on keyboards, expansion of multimedia, medical data privacy policy development, impact of molecular biology on knowledge and treatment of neoplasms, and use of imaging and informatics to advance understanding of brain structure and function. Key developments since 1998 include the huge increase in publicly available electronic information; acknowledgement by leaders in government and science of the importance of biomedical informatics to societal goals for health, health care, and scientific discovery; the influence of the public in promoting clinical research transparency and free access to government-funded research results; the long-awaited arrival of electronic health records; and the “Cloud” as a 21st century reformulation of contracting out the computer center. Conclusions There are many challenging and important problems that deserve the attention of the informatics community. Informatics researchers will be best served by embracing a very broad definition of medical informatics and by promoting public understanding of the field. PMID:27199193

76 FR 24036 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-29

... personal privacy. Name of Committee: Center for Scientific Review Special Emphasis Panel, Brain Disorders... Integrated Review Group, Biomedical Computing and Health Informatics Study Section. Date: June 7-8, 2011...

Harnessing Biomedical Natural Language Processing Tools to Identify Medicinal Plant Knowledge from Historical Texts.

PubMed

Sharma, Vivekanand; Law, Wayne; Balick, Michael J; Sarkar, Indra Neil

2017-01-01

The growing amount of data describing historical medicinal uses of plants from digitization efforts provides the opportunity to develop systematic approaches for identifying potential plant-based therapies. However, the task of cataloguing plant use information from natural language text is a challenging task for ethnobotanists. To date, there have been only limited adoption of informatics approaches used for supporting the identification of ethnobotanical information associated with medicinal uses. This study explored the feasibility of using biomedical terminologies and natural language processing approaches for extracting relevant plant-associated therapeutic use information from historical biodiversity literature collection available from the Biodiversity Heritage Library. The results from this preliminary study suggest that there is potential utility of informatics methods to identify medicinal plant knowledge from digitized resources as well as highlight opportunities for improvement.

Harnessing Biomedical Natural Language Processing Tools to Identify Medicinal Plant Knowledge from Historical Texts

PubMed Central

Sharma, Vivekanand; Law, Wayne; Balick, Michael J.; Sarkar, Indra Neil

2017-01-01

The growing amount of data describing historical medicinal uses of plants from digitization efforts provides the opportunity to develop systematic approaches for identifying potential plant-based therapies. However, the task of cataloguing plant use information from natural language text is a challenging task for ethnobotanists. To date, there have been only limited adoption of informatics approaches used for supporting the identification of ethnobotanical information associated with medicinal uses. This study explored the feasibility of using biomedical terminologies and natural language processing approaches for extracting relevant plant-associated therapeutic use information from historical biodiversity literature collection available from the Biodiversity Heritage Library. The results from this preliminary study suggest that there is potential utility of informatics methods to identify medicinal plant knowledge from digitized resources as well as highlight opportunities for improvement. PMID:29854223

National Mesothelioma Virtual Bank: a standard based biospecimen and clinical data resource to enhance translational research.

PubMed

Amin, Waqas; Parwani, Anil V; Schmandt, Linda; Mohanty, Sambit K; Farhat, Ghada; Pople, Andrew K; Winters, Sharon B; Whelan, Nancy B; Schneider, Althea M; Milnes, John T; Valdivieso, Federico A; Feldman, Michael; Pass, Harvey I; Dhir, Rajiv; Melamed, Jonathan; Becich, Michael J

2008-08-13

Advances in translational research have led to the need for well characterized biospecimens for research. The National Mesothelioma Virtual Bank is an initiative which collects annotated datasets relevant to human mesothelioma to develop an enterprising biospecimen resource to fulfill researchers' need. The National Mesothelioma Virtual Bank architecture is based on three major components: (a) common data elements (based on College of American Pathologists protocol and National North American Association of Central Cancer Registries standards), (b) clinical and epidemiologic data annotation, and (c) data query tools. These tools work interoperably to standardize the entire process of annotation. The National Mesothelioma Virtual Bank tool is based upon the caTISSUE Clinical Annotation Engine, developed by the University of Pittsburgh in cooperation with the Cancer Biomedical Informatics Grid (caBIG, see http://cabig.nci.nih.gov). This application provides a web-based system for annotating, importing and searching mesothelioma cases. The underlying information model is constructed utilizing Unified Modeling Language class diagrams, hierarchical relationships and Enterprise Architect software. The database provides researchers real-time access to richly annotated specimens and integral information related to mesothelioma. The data disclosed is tightly regulated depending upon users' authorization and depending on the participating institute that is amenable to the local Institutional Review Board and regulation committee reviews. The National Mesothelioma Virtual Bank currently has over 600 annotated cases available for researchers that include paraffin embedded tissues, tissue microarrays, serum and genomic DNA. The National Mesothelioma Virtual Bank is a virtual biospecimen registry with robust translational biomedical informatics support to facilitate basic science, clinical, and translational research. Furthermore, it protects patient privacy by disclosing only de-identified datasets to assure that biospecimens can be made accessible to researchers.

A current perspective on medical informatics and health sciences librarianship.

PubMed

Perry, Gerald J; Roderer, Nancy K; Assar, Soraya

2005-04-01

The article offers a current perspective on medical informatics and health sciences librarianship. The authors: (1) discuss how definitions of medical informatics have changed in relation to health sciences librarianship and the broader domain of information science; (2) compare the missions of health sciences librarianship and health sciences informatics, reviewing the characteristics of both disciplines; (3) propose a new definition of health sciences informatics; (4) consider the research agendas of both disciplines and the possibility that they have merged; and (5) conclude with some comments about actions and roles for health sciences librarians to flourish in the biomedical information environment of today and tomorrow. Boundaries are disappearing between the sources and types of and uses for health information managed by informaticians and librarians. Definitions of the professional domains of each have been impacted by these changes in information. Evolving definitions reflect the increasingly overlapping research agendas of both disciplines. Professionals in these disciplines are increasingly functioning collaboratively as "boundary spanners," incorporating human factors that unite technology with health care delivery.

It's all in the timing: calibrating temporal penalties for biomedical data sharing.

PubMed

Xia, Weiyi; Wan, Zhiyu; Yin, Zhijun; Gaupp, James; Liu, Yongtai; Clayton, Ellen Wright; Kantarcioglu, Murat; Vorobeychik, Yevgeniy; Malin, Bradley A

2018-01-01

Biomedical science is driven by datasets that are being accumulated at an unprecedented rate, with ever-growing volume and richness. There are various initiatives to make these datasets more widely available to recipients who sign Data Use Certificate agreements, whereby penalties are levied for violations. A particularly popular penalty is the temporary revocation, often for several months, of the recipient's data usage rights. This policy is based on the assumption that the value of biomedical research data depreciates significantly over time; however, no studies have been performed to substantiate this belief. This study investigates whether this assumption holds true and the data science policy implications. This study tests the hypothesis that the value of data for scientific investigators, in terms of the impact of the publications based on the data, decreases over time. The hypothesis is tested formally through a mixed linear effects model using approximately 1200 publications between 2007 and 2013 that used datasets from the Database of Genotypes and Phenotypes, a data-sharing initiative of the National Institutes of Health. The analysis shows that the impact factors for publications based on Database of Genotypes and Phenotypes datasets depreciate in a statistically significant manner. However, we further discover that the depreciation rate is slow, only ∼10% per year, on average. The enduring value of data for subsequent studies implies that revoking usage for short periods of time may not sufficiently deter those who would violate Data Use Certificate agreements and that alternative penalty mechanisms may need to be invoked. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Quantitative and Qualitative Evaluation of The Structural Designing of Medical Informatics Dynamic Encyclopedia.

PubMed

Safdari, Reza; Shahmoradi, Leila; Hosseini-Beheshti, Molouk-Sadat; Nejad, Ahmadreza Farzaneh; Hosseiniravandi, Mohammad

2015-10-01

Encyclopedias and their compilation have become so prevalent as a valid cultural medium in the world. The daily development of computer industry and the expansion of various sciences have made indispensable the compilation of electronic, specialized encyclopedias, especially the web-based ones. This is an applied-developmental study conducted in 2014. First, the main terms in the field of medical informatics were gathered using MeSH Online 2014 and the supplementary terms of each were determined, and then the tree diagram of the terms was drawn based on their relationship in MeSH. Based on the studies done by the researchers, the tree diagram of the encyclopedia was drawn with respect to the existing areas in this field, and the terms gathered were put in related domains. In MeSH, 75 preferred terms together with 249 supplementary ones were indexed. One of the informatics' sub-branches is biomedical informatics and health which itself consists of three sub-divisions of bioinformatics, clinical informatics, and health informatics. Medical informatics which is a subdivision of clinical informatics has developed from the three fields of medical sciences, management and social sciences, and computational sciences and mathematics. Medical Informatics is created of confluence and fusion and applications of the three major scientific branches include health and biological sciences, social sciences and management sciences, computing and mathematical sciences, and according to that the structure of MeSH is weak for future development of Encyclopedia of Medical Informatics.

Silver Anniversary: 25 Editions of the IMIA Yearbook.

PubMed

Lehmann, C U; Jaulent, M-C; Séroussi, B

2016-05-20

To provide an editorial introduction into the special 25th anniversary edition of the IMIA Yearbook of Medical Informatics with discussion of the significance of the Yearbook, past and current editorial teams, and a look into the future. A brief overview of the 2016 anniversary edition of the Yearbook allows for a discussion of the significance and value of the Yearbook to the Biomedical Informatics community as well as a review of changes in Yearbook team and format over time. The IMIA Yearbook celebrates its 25th edition bearing witness to the quality of the IMIA brand, the Yearbook content, as well as to the dedication of and the inordinate amount of labor from the authors and editors of the Yearbook. Editorial teams are to be applauded for their hard work and for their foresight in steering the Yearbook from a paperback to an open access online publication. The special edition provides reviews of past editorials with the knowledge of today. The IMIA Yearbook celebrates a remarkable milestone providing a testament to the maturity of the Biomedical Informatics field. Informaticians across the world are encouraged to thank past editorial teams and celebrate with IMIA.

IMIA Educational Recommendations and Nursing Informatics.

PubMed

Mantas, John; Hasman, Arie

2017-01-01

The updated version of the IMIA educational recommendations has given an adequate guidelines platform for developing educational programs in Biomedical and Health Informatics at all levels of education, vocational training, and distance learning. This chapter will provide a brief introduction of the recommendations pinpointing aspects for developing and assessing educational programs. We will provide a review of the existing feedback we have acquired during the IMIA site visits of accrediting educational programs at a worldwide level and discuss implementations issues. A brief overview of existing academic programs in Europe, North America and in other regions, especially for programs related to Nursing and to Nursing Informatics is provided. Finally, we will draw conclusions as how the IMIA recommendations may be required to be fitted into the specific needs of the Nursing Informatics and the needs of the Nursing professionals when they apply the recommendations to their academic and/or hospital/professional environments.

Big data for health.

PubMed

Andreu-Perez, Javier; Poon, Carmen C Y; Merrifield, Robert D; Wong, Stephen T C; Yang, Guang-Zhong

2015-07-01

This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled.

Information and informatics literacy: skills, timing, and estimates of competence.

PubMed

Scott, C S; Schaad, D C; Mandel, L S; Brock, D M; Kim, S

2000-01-01

Computing and biomedical informatics technologies are providing almost instantaneous access to vast amounts of possibly relevant information. Although students are entering medical school with increasingly sophisticated basic technological skills, medical educators must determine what curricular enhancements are needed to prepare learners for the world of electronic information. The purpose was to examine opinions of academic affairs and informatics administrators, curriculum deans and recently matriculated medical students about prematriculation competence and medical education learning expectations. Two surveys were administered: an Information Literacy Survey for curriculum/informatics deans and a Computing Skills Survey for entering medical students. Results highlight differences of opinion about entering competencies. They also indicate that medical school administrators believe that most basic information skills fall within the domain of undergraduate medical education. Further investigations are needed to determine precise entry-level skills and whether information literacy will increase as a result of rising levels of technical competence.

Toward a formalization of the process to select IMIA Yearbook best papers.

PubMed

Lamy, J-B; Séroussi, B; Griffon, N; Kerdelhué, G; Jaulent, M-C; Bouaud, J

2015-01-01

Each year, the International Medical Informatics Association Yearbook recognizes significant scientific papers, labelled as "best papers", published the previous year in the subfields of biomedical informatics that correspond to the different section topics of the journal. For each section, about fifteen pre-selected "candidate" best papers are externally peer-reviewed to select the actual best papers. Although based on the available literature, little is known about the pre-selection process. To move toward an explicit formalization of the candidate best papers selection process to reduce variability in the literature search across sections and over years. A methodological framework is proposed to build for each section topic specific queries tailored to PubMed and Web of Science citation databases. The two sets of returned papers are merged and reviewed by two independent section editors and citations are tagged as "discarded", "pending", and "kept". A protocolized consolidation step is then jointly conducted to resolve conflicts. A bibliographic software tool, BibReview, was developed to support the whole process. The proposed search strategy was fully applied to the Decision Support section of the 2013 edition of the Yearbook. For this section, 1124 references were returned (689 PubMed-specific, 254 WoS-specific, 181 common to both databases) among which the 15 candidate best papers were selected. The search strategy for determining candidate best papers for an IMIA Yearbook's section is now explicitly specified and allows for reproducibility. However, some aspects of the whole process remain reviewer-dependent, mostly because there is no characterization of a "best paper".

Human Connectome Project Informatics: quality control, database services, and data visualization

PubMed Central

Marcus, Daniel S.; Harms, Michael P.; Snyder, Abraham Z.; Jenkinson, Mark; Wilson, J Anthony; Glasser, Matthew F.; Barch, Deanna M.; Archie, Kevin A.; Burgess, Gregory C.; Ramaratnam, Mohana; Hodge, Michael; Horton, William; Herrick, Rick; Olsen, Timothy; McKay, Michael; House, Matthew; Hileman, Michael; Reid, Erin; Harwell, John; Coalson, Timothy; Schindler, Jon; Elam, Jennifer S.; Curtiss, Sandra W.; Van Essen, David C.

2013-01-01

The Human Connectome Project (HCP) has developed protocols, standard operating and quality control procedures, and a suite of informatics tools to enable high throughput data collection, data sharing, automated data processing and analysis, and data mining and visualization. Quality control procedures include methods to maintain data collection consistency over time, to measure head motion, and to establish quantitative modality-specific overall quality assessments. Database services developed as customizations of the XNAT imaging informatics platform support both internal daily operations and open access data sharing. The Connectome Workbench visualization environment enables user interaction with HCP data and is increasingly integrated with the HCP's database services. Here we describe the current state of these procedures and tools and their application in the ongoing HCP study. PMID:23707591

The caBIG Terminology Review Process

PubMed Central

Cimino, James J.; Hayamizu, Terry F.; Bodenreider, Olivier; Davis, Brian; Stafford, Grace A.; Ringwald, Martin

2009-01-01

The National Cancer Institute (NCI) is developing an integrated biomedical informatics infrastructure, the cancer Biomedical Informatics Grid (caBIG®), to support collaboration within the cancer research community. A key part of the caBIG architecture is the establishment of terminology standards for representing data. In order to evaluate the suitability of existing controlled terminologies, the caBIG Vocabulary and Data Elements Workspace (VCDE WS) working group has developed a set of criteria that serve to assess a terminology's structure, content, documentation, and editorial process. This paper describes the evolution of these criteria and the results of their use in evaluating four standard terminologies: the Gene Ontology (GO), the NCI Thesaurus (NCIt), the Common Terminology for Adverse Events (known as CTCAE), and the laboratory portion of the Logical Objects, Identifiers, Names and Codes (LOINC). The resulting caBIG criteria are presented as a matrix that may be applicable to any terminology standardization effort. PMID:19154797

Informatics in radiology: automated structured reporting of imaging findings using the AIM standard and XML.

PubMed

Zimmerman, Stefan L; Kim, Woojin; Boonn, William W

2011-01-01

Quantitative and descriptive imaging data are a vital component of the radiology report and are frequently of paramount importance to the ordering physician. Unfortunately, current methods of recording these data in the report are both inefficient and error prone. In addition, the free-text, unstructured format of a radiology report makes aggregate analysis of data from multiple reports difficult or even impossible without manual intervention. A structured reporting work flow has been developed that allows quantitative data created at an advanced imaging workstation to be seamlessly integrated into the radiology report with minimal radiologist intervention. As an intermediary step between the workstation and the reporting software, quantitative and descriptive data are converted into an extensible markup language (XML) file in a standardized format specified by the Annotation and Image Markup (AIM) project of the National Institutes of Health Cancer Biomedical Informatics Grid. The AIM standard was created to allow image annotation data to be stored in a uniform machine-readable format. These XML files containing imaging data can also be stored on a local database for data mining and analysis. This structured work flow solution has the potential to improve radiologist efficiency, reduce errors, and facilitate storage of quantitative and descriptive imaging data for research. Copyright © RSNA, 2011.

Development of the Lymphoma Enterprise Architecture Database: A caBIG(tm) Silver level compliant System

PubMed Central

Huang, Taoying; Shenoy, Pareen J.; Sinha, Rajni; Graiser, Michael; Bumpers, Kevin W.; Flowers, Christopher R.

2009-01-01

Lymphomas are the fifth most common cancer in United States with numerous histological subtypes. Integrating existing clinical information on lymphoma patients provides a platform for understanding biological variability in presentation and treatment response and aids development of novel therapies. We developed a cancer Biomedical Informatics Grid™ (caBIG™) Silver level compliant lymphoma database, called the Lymphoma Enterprise Architecture Data-system™ (LEAD™), which integrates the pathology, pharmacy, laboratory, cancer registry, clinical trials, and clinical data from institutional databases. We utilized the Cancer Common Ontological Representation Environment Software Development Kit (caCORE SDK) provided by National Cancer Institute’s Center for Bioinformatics to establish the LEAD™ platform for data management. The caCORE SDK generated system utilizes an n-tier architecture with open Application Programming Interfaces, controlled vocabularies, and registered metadata to achieve semantic integration across multiple cancer databases. We demonstrated that the data elements and structures within LEAD™ could be used to manage clinical research data from phase 1 clinical trials, cohort studies, and registry data from the Surveillance Epidemiology and End Results database. This work provides a clear example of how semantic technologies from caBIG™ can be applied to support a wide range of clinical and research tasks, and integrate data from disparate systems into a single architecture. This illustrates the central importance of caBIG™ to the management of clinical and biological data. PMID:19492074

Development of the Lymphoma Enterprise Architecture Database: a caBIG Silver level compliant system.

PubMed

Huang, Taoying; Shenoy, Pareen J; Sinha, Rajni; Graiser, Michael; Bumpers, Kevin W; Flowers, Christopher R

2009-04-03

Lymphomas are the fifth most common cancer in United States with numerous histological subtypes. Integrating existing clinical information on lymphoma patients provides a platform for understanding biological variability in presentation and treatment response and aids development of novel therapies. We developed a cancer Biomedical Informatics Grid (caBIG) Silver level compliant lymphoma database, called the Lymphoma Enterprise Architecture Data-system (LEAD), which integrates the pathology, pharmacy, laboratory, cancer registry, clinical trials, and clinical data from institutional databases. We utilized the Cancer Common Ontological Representation Environment Software Development Kit (caCORE SDK) provided by National Cancer Institute's Center for Bioinformatics to establish the LEAD platform for data management. The caCORE SDK generated system utilizes an n-tier architecture with open Application Programming Interfaces, controlled vocabularies, and registered metadata to achieve semantic integration across multiple cancer databases. We demonstrated that the data elements and structures within LEAD could be used to manage clinical research data from phase 1 clinical trials, cohort studies, and registry data from the Surveillance Epidemiology and End Results database. This work provides a clear example of how semantic technologies from caBIG can be applied to support a wide range of clinical and research tasks, and integrate data from disparate systems into a single architecture. This illustrates the central importance of caBIG to the management of clinical and biological data.

TRIAD: The Translational Research Informatics and Data Management Grid

PubMed Central

Payne, P.; Ervin, D.; Dhaval, R.; Borlawsky, T.; Lai, A.

2011-01-01

Objective Multi-disciplinary and multi-site biomedical research programs frequently require infrastructures capable of enabling the collection, management, analysis, and dissemination of heterogeneous, multi-dimensional, and distributed data and knowledge collections spanning organizational boundaries. We report on the design and initial deployment of an extensible biomedical informatics platform that is intended to address such requirements. Methods A common approach to distributed data, information, and knowledge management needs in the healthcare and life science settings is the deployment and use of a service-oriented architecture (SOA). Such SOA technologies provide for strongly-typed, semantically annotated, and stateful data and analytical services that can be combined into data and knowledge integration and analysis “pipelines.” Using this overall design pattern, we have implemented and evaluated an extensible SOA platform for clinical and translational science applications known as the Translational Research Informatics and Data-management grid (TRIAD). TRIAD is a derivative and extension of the caGrid middleware and has an emphasis on supporting agile “working interoperability” between data, information, and knowledge resources. Results Based upon initial verification and validation studies conducted in the context of a collection of driving clinical and translational research problems, we have been able to demonstrate that TRIAD achieves agile “working interoperability” between distributed data and knowledge sources. Conclusion Informed by our initial verification and validation studies, we believe TRIAD provides an example instance of a lightweight and readily adoptable approach to the use of SOA technologies in the clinical and translational research setting. Furthermore, our initial use cases illustrate the importance and efficacy of enabling “working interoperability” in heterogeneous biomedical environments. PMID:23616879

TRIAD: The Translational Research Informatics and Data Management Grid.

PubMed

Payne, P; Ervin, D; Dhaval, R; Borlawsky, T; Lai, A

2011-01-01

Multi-disciplinary and multi-site biomedical research programs frequently require infrastructures capable of enabling the collection, management, analysis, and dissemination of heterogeneous, multi-dimensional, and distributed data and knowledge collections spanning organizational boundaries. We report on the design and initial deployment of an extensible biomedical informatics platform that is intended to address such requirements. A common approach to distributed data, information, and knowledge management needs in the healthcare and life science settings is the deployment and use of a service-oriented architecture (SOA). Such SOA technologies provide for strongly-typed, semantically annotated, and stateful data and analytical services that can be combined into data and knowledge integration and analysis "pipelines." Using this overall design pattern, we have implemented and evaluated an extensible SOA platform for clinical and translational science applications known as the Translational Research Informatics and Data-management grid (TRIAD). TRIAD is a derivative and extension of the caGrid middleware and has an emphasis on supporting agile "working interoperability" between data, information, and knowledge resources. Based upon initial verification and validation studies conducted in the context of a collection of driving clinical and translational research problems, we have been able to demonstrate that TRIAD achieves agile "working interoperability" between distributed data and knowledge sources. Informed by our initial verification and validation studies, we believe TRIAD provides an example instance of a lightweight and readily adoptable approach to the use of SOA technologies in the clinical and translational research setting. Furthermore, our initial use cases illustrate the importance and efficacy of enabling "working interoperability" in heterogeneous biomedical environments.

State of the art and trends for digital pathology.

PubMed

García Rojo, Marcial

2012-01-01

Anatomic pathology is a medical specialty where both information management systems and digital images systems paly a most important role. Digital pathology is a new concept that considers all uses of this information, including diagnosis, biomedical research and education. Virtual microscopy or whole slide imaging, resulting in digital slides, is an outreaching technology in anatomic pathology. Limiting factors in the expansion of virtual microscopy are formidable storage dimension, scanning speed, quality of image and cultural change. Anatomic pathology data and images should be an important part of the patient electronic health records as well as of clinical data warehouse, epidemiological or biomedical research databases, and platforms dedicated to translational medicine. Integrating anatomic pathology to the "healthcare enterprise" can only be achieved using existing and emerging medical informatics standards like Digital Imaging and Communications in Medicine (DICOM®¹), Health Level Seven (HL7®), and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT®), following the recommendations of Integrating the Healthcare Enterprise (IHE®). The consequences of the full digitalization of pathology departments are hard to foresee, but short term issues have arisen that imply interesting challenges for health care standards bodies.

Bio and health informatics meets cloud : BioVLab as an example.

PubMed

Chae, Heejoon; Jung, Inuk; Lee, Hyungro; Marru, Suresh; Lee, Seong-Whan; Kim, Sun

2013-01-01

The exponential increase of genomic data brought by the advent of the next or the third generation sequencing (NGS) technologies and the dramatic drop in sequencing cost have driven biological and medical sciences to data-driven sciences. This revolutionary paradigm shift comes with challenges in terms of data transfer, storage, computation, and analysis of big bio/medical data. Cloud computing is a service model sharing a pool of configurable resources, which is a suitable workbench to address these challenges. From the medical or biological perspective, providing computing power and storage is the most attractive feature of cloud computing in handling the ever increasing biological data. As data increases in size, many research organizations start to experience the lack of computing power, which becomes a major hurdle in achieving research goals. In this paper, we review the features of publically available bio and health cloud systems in terms of graphical user interface, external data integration, security and extensibility of features. We then discuss about issues and limitations of current cloud systems and conclude with suggestion of a biological cloud environment concept, which can be defined as a total workbench environment assembling computational tools and databases for analyzing bio/medical big data in particular application domains.

77 FR 59933 - Center for Scientific Review; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-01

...; Biomedical Computing and Health Informatics Study Section. Date: October 11, 2012. Time: 12:00 p.m. to 4:00 p... funding cycle. (Catalogue of Federal Domestic Assistance Program Nos. 93.306, Comparative Medicine; 93.333...

Information and informatics literacies of first-year medical students

PubMed Central

Bouquin, Daina R.; Tmanova, Lyubov L.; Wright, Drew

2015-01-01

Purpose The study evaluated medical students' familiarity with information literacy and informatics during the health sciences library orientation. Methods A survey was fielded at the start of the 2013 school year. Results Seventy-two of 77 students (94%) completed the survey. Over one-half (57%) expected to use library research materials and services. About half (43%) expected to use library physical space. Students preferred accessing biomedical research on laptops and learning via online-asynchronous modes. Conclusions The library identified areas for service development and outreach to medical students and academic departments. PMID:26512221

A current perspective on medical informatics and health sciences librarianship

PubMed Central

Perry, Gerald J.; Roderer, Nancy K.; Assar, Soraya

2005-01-01

Objective: The article offers a current perspective on medical informatics and health sciences librarianship. Narrative: The authors: (1) discuss how definitions of medical informatics have changed in relation to health sciences librarianship and the broader domain of information science; (2) compare the missions of health sciences librarianship and health sciences informatics, reviewing the characteristics of both disciplines; (3) propose a new definition of health sciences informatics; (4) consider the research agendas of both disciplines and the possibility that they have merged; and (5) conclude with some comments about actions and roles for health sciences librarians to flourish in the biomedical information environment of today and tomorrow. Summary: Boundaries are disappearing between the sources and types of and uses for health information managed by informaticians and librarians. Definitions of the professional domains of each have been impacted by these changes in information. Evolving definitions reflect the increasingly overlapping research agendas of both disciplines. Professionals in these disciplines are increasingly functioning collaboratively as “boundary spanners,” incorporating human factors that unite technology with health care delivery. PMID:15858622

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

Informatic innovations in glycobiology: relevance to drug discovery.

PubMed

Mamitsuka, Hiroshi

2008-02-01

The recent development and applications of tree-based informatics on glycans have accelerated the biological analysis on glycans, particularly from structural viewpoints. We review three major aspects of recent informatics innovations on glycan structures: maturity of well-organized databases on glycan structures linking with other biological information, implementation of glycan structure matching algorithms and extensive development of methods for mining frequent patterns from glycan structures.

Education in Biomedical and Health Informatics in the Web 3.0 Era: Standards for data, curricula, and activities. Contribution of the IMIA Working Group on Health and Medical Informatics Education.

PubMed

Otero, P; Hersh, W

2011-01-01

Web 3.0 is transforming the World Wide Web by allowing knowledge and reasoning to be gleaned from its content. Describe a new scenario in education and training known as "Education 3.0" that can help in the promotion of learning in health informatics in a collaborative way. Review of the current standards available for curricula and learning activities in in Biomedical and Health Informatics (BMHI) for a Web 3.0 scenario. A new scenario known as "Education 3.0" can provide open educational resources created and reused throughout different institutions and improved by means of an international collaborative knowledge powered by the use of E-learning. Currently there are standards that could be used in identifying and deliver content in education in BMHI in the semantic web era such as Resource Description Format (RDF), Web Ontology Language (OWL) and Sharable Content Object Reference Model (SCORM). In addition, there are other standards to support healthcare education and training. There are few experiences in the use of standards in e-learning in BMHI published in the literature. Web 3.0 can propose new approaches to building the BMHI workforce so there is a need to build tools as knowledge infrastructure to leverage it. The usefulness of standards in the content and competencies of training programs in BMHI needs more experience and research so as to promote the interoperability and sharing of resources in this growing discipline.

Historical Roots of International Biomedical and Health Informatics: The Road to IFIP-TC4 and IMIA through Cybernetic Medicine and the Elsinore Meetings.

PubMed

Kulikowski, C A

2017-08-01

Background: It is 50 years since the International Federation of Information Processing (IFIP) Societies approved the formation of a new Technical Committee (TC) 4 on Medical Information Processing under the leadership of Professor Francois Grémy, which was the direct precursor of the International Medical Informatics Association (IMIA). Objectives: The goals of this paper are to give a very brief overview of early international developments leading to informatics in medicine, with the origins of the applications of computers to medicine in the USA and Europe, and two meetings - of the International Society of Cybernetic Medicine, and the Elsinore Meetings on Hospital Information Systems-that took place in 1966. These set the stage for the formation of IFIP-TC4 the following year, with later sponsorship of the first MEDINFO in 1974, setting the path for the evolution to IMIA. Methods: This paper reviews and analyzes some of the earliest research and publications, together with two critical contrasting meetings in 1966 involving international activities in what evolved into biomedical and health informatics in terms of their probable influence on the formation of IFIP-TC4. Conclusion: The formation of IFIP-TC 4 in 1967 by Francois Grémy arose out of his concerns for merging, at an international level, the diverse strands from the more abstract work on cybernetic medicine and its basis in biophysical and neural modeling, with the more concrete and health-oriented medical information processing that was developing at the time for hospitals and clinical decision-making. Georg Thieme Verlag KG Stuttgart.

Quantitative and Qualitative Evaluation of The Structural Designing of Medical Informatics Dynamic Encyclopedia

PubMed Central

Safdari, Reza; Shahmoradi, Leila; Hosseini-beheshti, Molouk-sadat; Nejad, Ahmadreza Farzaneh; Hosseiniravandi, Mohammad

2015-01-01

Introduction: Encyclopedias and their compilation have become so prevalent as a valid cultural medium in the world. The daily development of computer industry and the expansion of various sciences have made indispensable the compilation of electronic, specialized encyclopedias, especially the web-based ones. Materials and Methods: This is an applied-developmental study conducted in 2014. First, the main terms in the field of medical informatics were gathered using MeSH Online 2014 and the supplementary terms of each were determined, and then the tree diagram of the terms was drawn based on their relationship in MeSH. Based on the studies done by the researchers, the tree diagram of the encyclopedia was drawn with respect to the existing areas in this field, and the terms gathered were put in related domains. Findings: In MeSH, 75 preferred terms together with 249 supplementary ones were indexed. One of the informatics’ sub-branches is biomedical informatics and health which itself consists of three sub-divisions of bioinformatics, clinical informatics, and health informatics. Medical informatics which is a subdivision of clinical informatics has developed from the three fields of medical sciences, management and social sciences, and computational sciences and mathematics. Results and Discussion: Medical Informatics is created of confluence and fusion and applications of the three major scientific branches include health and biological sciences, social sciences and management sciences, computing and mathematical sciences, and according to that the structure of MeSH is weak for future development of Encyclopedia of Medical Informatics. PMID:26635440

Health system informatics.

PubMed

Felkey, B G

1997-02-01

The application of informatics in a health system in general and to pharmacy in particular is discussed. Informatics is the use of information technology to enhance the quality of care, facilitate accountability, and assist in cost containment. Tying the pieces of health care into a seamless system using informatics principles yields a more rational approach to caregiving. A four-layer hierarchy of information systems can be found in any health system: layer 1, the foundational layer formed by a transaction-processing system; 2, the management information system; 3, decision support; and 4, advanced informatics applications such as expert systems. Other industries appear to be ahead of health care in investing in informatics applications. Pharmacy is one of the key health care professions that must adopt informatics. A stepwise structure for pharmacy informatics has been proposed; it consists of establishing a relationship with the patient, establishing a database, listing and ranking problems, choosing among alternatives, and planning and monitoring. Informatics should be approached by determining where the department is going strategically. Informatics standards will be needed. Pharmacists will need to use informatics to enhance their worth on the health care team and to improve patient care.

Big data: the next frontier for innovation in therapeutics and healthcare.

PubMed

Issa, Naiem T; Byers, Stephen W; Dakshanamurthy, Sivanesan

2014-05-01

Advancements in genomics and personalized medicine not only effect healthcare delivery from patient and provider standpoints, but also reshape biomedical discovery. We are in the era of the '-omics', wherein an individual's genome, transcriptome, proteome and metabolome can be scrutinized to the finest resolution to paint a personalized biochemical fingerprint that enables tailored treatments, prognoses, risk factors, etc. Digitization of this information parlays into 'big data' informatics-driven evidence-based medical practice. While individualized patient management is a key beneficiary of next-generation medical informatics, this data also harbors a wealth of novel therapeutic discoveries waiting to be uncovered. 'Big data' informatics allows for networks-driven systems pharmacodynamics whereby drug information can be coupled to cellular- and organ-level physiology for determining whole-body outcomes. Patient '-omics' data can be integrated for ontology-based data-mining for the discovery of new biological associations and drug targets. Here we highlight the potential of 'big data' informatics for clinical pharmacology.

Big data: the next frontier for innovation in therapeutics and healthcare

PubMed Central

Issa, Naiem T; Byers, Stephen W; Dakshanamurthy, Sivanesan

2015-01-01

Advancements in genomics and personalized medicine not only effect healthcare delivery from patient and provider standpoints, but also reshape biomedical discovery. We are in the era of the “-omics”, wherein an individual’s genome, transcriptome, proteome and metabolome can be scrutinized to the finest resolution to paint a personalized biochemical fingerprint that enables tailored treatments, prognoses, risk factors, etc. Digitization of this information parlays into “big data” informatics-driven evidence-based medical practice. While individualized patient management is a key beneficiary of next-generation medical informatics, this data also harbors a wealth of novel therapeutic discoveries waiting to be uncovered. “Big data” informatics allows for networks-driven systems pharmacodynamics whereby drug information can be coupled to cellular- and organ-level physiology for determining whole-body outcomes. Patient “-omics” data can be integrated for ontology-based data-mining for the discovery of new biological associations and drug targets. Here we highlight the potential of “big data” informatics for clinical pharmacology. PMID:24702684

For 481 biomedical open access journals, articles are not searchable in the Directory of Open Access Journals nor in conventional biomedical databases.

PubMed

Liljekvist, Mads Svane; Andresen, Kristoffer; Pommergaard, Hans-Christian; Rosenberg, Jacob

2015-01-01

Background. Open access (OA) journals allows access to research papers free of charge to the reader. Traditionally, biomedical researchers use databases like MEDLINE and EMBASE to discover new advances. However, biomedical OA journals might not fulfill such databases' criteria, hindering dissemination. The Directory of Open Access Journals (DOAJ) is a database exclusively listing OA journals. The aim of this study was to investigate DOAJ's coverage of biomedical OA journals compared with the conventional biomedical databases. Methods. Information on all journals listed in four conventional biomedical databases (MEDLINE, PubMed Central, EMBASE and SCOPUS) and DOAJ were gathered. Journals were included if they were (1) actively publishing, (2) full OA, (3) prospectively indexed in one or more database, and (4) of biomedical subject. Impact factor and journal language were also collected. DOAJ was compared with conventional databases regarding the proportion of journals covered, along with their impact factor and publishing language. The proportion of journals with articles indexed by DOAJ was determined. Results. In total, 3,236 biomedical OA journals were included in the study. Of the included journals, 86.7% were listed in DOAJ. Combined, the conventional biomedical databases listed 75.0% of the journals; 18.7% in MEDLINE; 36.5% in PubMed Central; 51.5% in SCOPUS and 50.6% in EMBASE. Of the journals in DOAJ, 88.7% published in English and 20.6% had received impact factor for 2012 compared with 93.5% and 26.0%, respectively, for journals in the conventional biomedical databases. A subset of 51.1% and 48.5% of the journals in DOAJ had articles indexed from 2012 and 2013, respectively. Of journals exclusively listed in DOAJ, one journal had received an impact factor for 2012, and 59.6% of the journals had no content from 2013 indexed in DOAJ. Conclusions. DOAJ is the most complete registry of biomedical OA journals compared with five conventional biomedical databases. However, DOAJ only indexes articles for half of the biomedical journals listed, making it an incomplete source for biomedical research papers in general.

The role of ethics in information technology decisions: a case-based approach to biomedical informatics education.

PubMed

Anderson, James G

2004-03-18

The purpose of this paper is to propose a case-based approach to instruction regarding ethical issues raised by the use of information technology (IT) in healthcare. These issues are rarely addressed in graduate degree and continuing professional education programs in health informatics. There are important reasons why ethical issues need to be addressed in informatics training. Ethical issues raised by the introduction of information technology affect practice and are ubiquitous. These issues are frequently among the most challenging to young practitioners who are ill prepared to deal with them in practice. First, the paper provides an overview of methods of moral reasoning that can be used to identify and analyze ethical problems in health informatics. Second, we provide a framework for defining cases that involve ethical issues and outline major issues raised by the use of information technology. Specific cases are used as examples of new dilemmas that are posed by the introduction of information technology in healthcare. These cases are used to illustrate how ethics can be integrated with the other elements of informatics training. The cases discussed here reflect day-to-day situations that arise in health settings that require decisions. Third, an approach that can be used to teach ethics in health informatics programs is outlined and illustrated.

Big Data and Biomedical Informatics: A Challenging Opportunity

PubMed Central

2014-01-01

Summary Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations. PMID:24853034

Big data and biomedical informatics: a challenging opportunity.

PubMed

Bellazzi, R

2014-05-22

Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations.

Nursing Informatics Certification Worldwide: History, Pathway, Roles, and Motivation

PubMed Central

Cummins, M. R.; Gundlapalli, A. V.; Murray, P.; Park, H.-A.; Lehmann, C. U.

2016-01-01

Summary Introduction Official recognition and certification for informatics professionals are essential aspects of workforce development. Objective: To describe the history, pathways, and nuances of certification in nursing informatics across the globe; compare and contrast those with board certification in clinical informatics for physicians. Methods (1) A review of the representative literature on informatics certification and related competencies for nurses and physicians, and relevant websites for nursing informatics associations and societies worldwide; (2) similarities and differences between certification processes for nurses and physicians, and (3) perspectives on roles for nursing informatics professionals in healthcare Results The literature search for ‘nursing informatics certification’ yielded few results in PubMed; Google Scholar yielded a large number of citations that extended to magazines and other non-peer reviewed sources. Worldwide, there are several nursing informatics associations, societies, and workgroups dedicated to nursing informatics associated with medical/health informatics societies. A formal certification program for nursing informatics appears to be available only in the United States. This certification was established in 1992, in concert with the formation and definition of nursing informatics as a specialty practice of nursing by the American Nurses Association. Although informatics is inherently interprofessional, certification pathways for nurses and physicians have developed separately, following long-standing professional structures, training, and pathways aligned with clinical licensure and direct patient care. There is substantial similarity with regard to the skills and competencies required for nurses and physicians to obtain informatics certification in their respective fields. Nurses may apply for and complete a certification examination if they have experience in the field, regardless of formal training. Increasing numbers of informatics nurses are pursuing certification. Conclusions The pathway to certification is clear and well-established for U.S. based informatics nurses. The motivation for obtaining and maintaining nursing informatics certification appears to be stronger for nurses who do not have an advanced informatics degree. The primary difference between nursing and physician certification pathways relates to the requirement of formal training and level of informatics practice. Nurse informatics certification requires no formal education or training and verifies knowledge and skill at a more basic level. Physician informatics certification validates informatics knowledge and skill at a more advanced level; currently this requires documentation of practice and experience in clinical informatics and in the future will require successful completion of an accredited two-year fellowship in clinical informatics. For the profession of nursing, a graduate degree in nursing or biomedical informatics validates specialty knowledge at a level more comparable to the physician certification. As the field of informatics and its professional organization structures mature, a common certification pathway may be appropriate. Nurses, physicians, and other healthcare professionals with informatics training and certification are needed to contribute their expertise in clinical operations, teaching, research, and executive leadership. PMID:27830261

Veterans Administration Databases

Cancer.gov

The Veterans Administration Information Resource Center provides database and informatics experts, customer service, expert advice, information products, and web technology to VA researchers and others.

The NIFSTD and BIRNLex Vocabularies: Building Comprehensive Ontologies for Neuroscience

PubMed Central

Bug, William J.; Ascoli, Giorgio A.; Grethe, Jeffrey S.; Gupta, Amarnath; Fennema-Notestine, Christine; Laird, Angela R.; Larson, Stephen D.; Rubin, Daniel; Shepherd, Gordon M.; Turner, Jessica A.; Martone, Maryann E.

2009-01-01

A critical component of the Neuroscience Information Framework (NIF) project is a consistent, flexible terminology for describing and retrieving neuroscience-relevant resources. Although the original NIF specification called for a loosely structured controlled vocabulary for describing neuroscience resources, as the NIF system evolved, the requirement for a formally structured ontology for neuroscience with sufficient granularity to describe and access a diverse collection of information became obvious. This requirement led to the NIF standardized (NIFSTD) ontology, a comprehensive collection of common neuroscience domain terminologies woven into an ontologically consistent, unified representation of the biomedical domains typically used to describe neuroscience data (e.g., anatomy, cell types, techniques), as well as digital resources (tools, databases) being created throughout the neuroscience community. NIFSTD builds upon a structure established by the BIRNLex, a lexicon of concepts covering clinical neuroimaging research developed by the Biomedical Informatics Research Network (BIRN) project. Each distinct domain module is represented using the Web Ontology Language (OWL). As much as has been practical, NIFSTD reuses existing community ontologies that cover the required biomedical domains, building the more specific concepts required to annotate NIF resources. By following this principle, an extensive vocabulary was assembled in a relatively short period of time for NIF information annotation, organization, and retrieval, in a form that promotes easy extension and modification. We report here on the structure of the NIFSTD, and its predecessor BIRNLex, the principles followed in its construction and provide examples of its use within NIF. PMID:18975148

The NIFSTD and BIRNLex vocabularies: building comprehensive ontologies for neuroscience.

PubMed

Bug, William J; Ascoli, Giorgio A; Grethe, Jeffrey S; Gupta, Amarnath; Fennema-Notestine, Christine; Laird, Angela R; Larson, Stephen D; Rubin, Daniel; Shepherd, Gordon M; Turner, Jessica A; Martone, Maryann E

2008-09-01

A critical component of the Neuroscience Information Framework (NIF) project is a consistent, flexible terminology for describing and retrieving neuroscience-relevant resources. Although the original NIF specification called for a loosely structured controlled vocabulary for describing neuroscience resources, as the NIF system evolved, the requirement for a formally structured ontology for neuroscience with sufficient granularity to describe and access a diverse collection of information became obvious. This requirement led to the NIF standardized (NIFSTD) ontology, a comprehensive collection of common neuroscience domain terminologies woven into an ontologically consistent, unified representation of the biomedical domains typically used to describe neuroscience data (e.g., anatomy, cell types, techniques), as well as digital resources (tools, databases) being created throughout the neuroscience community. NIFSTD builds upon a structure established by the BIRNLex, a lexicon of concepts covering clinical neuroimaging research developed by the Biomedical Informatics Research Network (BIRN) project. Each distinct domain module is represented using the Web Ontology Language (OWL). As much as has been practical, NIFSTD reuses existing community ontologies that cover the required biomedical domains, building the more specific concepts required to annotate NIF resources. By following this principle, an extensive vocabulary was assembled in a relatively short period of time for NIF information annotation, organization, and retrieval, in a form that promotes easy extension and modification. We report here on the structure of the NIFSTD, and its predecessor BIRNLex, the principles followed in its construction and provide examples of its use within NIF.

Grid-Enabled Measures

PubMed Central

Moser, Richard P.; Hesse, Bradford W.; Shaikh, Abdul R.; Courtney, Paul; Morgan, Glen; Augustson, Erik; Kobrin, Sarah; Levin, Kerry; Helba, Cynthia; Garner, David; Dunn, Marsha; Coa, Kisha

2011-01-01

Scientists are taking advantage of the Internet and collaborative web technology to accelerate discovery in a massively connected, participative environment —a phenomenon referred to by some as Science 2.0. As a new way of doing science, this phenomenon has the potential to push science forward in a more efficient manner than was previously possible. The Grid-Enabled Measures (GEM) database has been conceptualized as an instantiation of Science 2.0 principles by the National Cancer Institute with two overarching goals: (1) Promote the use of standardized measures, which are tied to theoretically based constructs; and (2) Facilitate the ability to share harmonized data resulting from the use of standardized measures. This is done by creating an online venue connected to the Cancer Biomedical Informatics Grid (caBIG®) where a virtual community of researchers can collaborate together and come to consensus on measures by rating, commenting and viewing meta-data about the measures and associated constructs. This paper will describe the web 2.0 principles on which the GEM database is based, describe its functionality, and discuss some of the important issues involved with creating the GEM database, such as the role of mutually agreed-on ontologies (i.e., knowledge categories and the relationships among these categories— for data sharing). PMID:21521586

For 481 biomedical open access journals, articles are not searchable in the Directory of Open Access Journals nor in conventional biomedical databases

PubMed Central

Andresen, Kristoffer; Pommergaard, Hans-Christian; Rosenberg, Jacob

2015-01-01

Background. Open access (OA) journals allows access to research papers free of charge to the reader. Traditionally, biomedical researchers use databases like MEDLINE and EMBASE to discover new advances. However, biomedical OA journals might not fulfill such databases’ criteria, hindering dissemination. The Directory of Open Access Journals (DOAJ) is a database exclusively listing OA journals. The aim of this study was to investigate DOAJ’s coverage of biomedical OA journals compared with the conventional biomedical databases. Methods. Information on all journals listed in four conventional biomedical databases (MEDLINE, PubMed Central, EMBASE and SCOPUS) and DOAJ were gathered. Journals were included if they were (1) actively publishing, (2) full OA, (3) prospectively indexed in one or more database, and (4) of biomedical subject. Impact factor and journal language were also collected. DOAJ was compared with conventional databases regarding the proportion of journals covered, along with their impact factor and publishing language. The proportion of journals with articles indexed by DOAJ was determined. Results. In total, 3,236 biomedical OA journals were included in the study. Of the included journals, 86.7% were listed in DOAJ. Combined, the conventional biomedical databases listed 75.0% of the journals; 18.7% in MEDLINE; 36.5% in PubMed Central; 51.5% in SCOPUS and 50.6% in EMBASE. Of the journals in DOAJ, 88.7% published in English and 20.6% had received impact factor for 2012 compared with 93.5% and 26.0%, respectively, for journals in the conventional biomedical databases. A subset of 51.1% and 48.5% of the journals in DOAJ had articles indexed from 2012 and 2013, respectively. Of journals exclusively listed in DOAJ, one journal had received an impact factor for 2012, and 59.6% of the journals had no content from 2013 indexed in DOAJ. Conclusions. DOAJ is the most complete registry of biomedical OA journals compared with five conventional biomedical databases. However, DOAJ only indexes articles for half of the biomedical journals listed, making it an incomplete source for biomedical research papers in general. PMID:26038727

Relational databases: a transparent framework for encouraging biology students to think informatically.

PubMed

Rice, Michael; Gladstone, William; Weir, Michael

2004-01-01

We discuss how relational databases constitute an ideal framework for representing and analyzing large-scale genomic data sets in biology. As a case study, we describe a Drosophila splice-site database that we recently developed at Wesleyan University for use in research and teaching. The database stores data about splice sites computed by a custom algorithm using Drosophila cDNA transcripts and genomic DNA and supports a set of procedures for analyzing splice-site sequence space. A generic Web interface permits the execution of the procedures with a variety of parameter settings and also supports custom structured query language queries. Moreover, new analytical procedures can be added by updating special metatables in the database without altering the Web interface. The database provides a powerful setting for students to develop informatic thinking skills.

Relational Databases: A Transparent Framework for Encouraging Biology Students To Think Informatically

PubMed Central

2004-01-01

We discuss how relational databases constitute an ideal framework for representing and analyzing large-scale genomic data sets in biology. As a case study, we describe a Drosophila splice-site database that we recently developed at Wesleyan University for use in research and teaching. The database stores data about splice sites computed by a custom algorithm using Drosophila cDNA transcripts and genomic DNA and supports a set of procedures for analyzing splice-site sequence space. A generic Web interface permits the execution of the procedures with a variety of parameter settings and also supports custom structured query language queries. Moreover, new analytical procedures can be added by updating special metatables in the database without altering the Web interface. The database provides a powerful setting for students to develop informatic thinking skills. PMID:15592597

Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure.

PubMed

P Tafti, Ahmad; Badger, Jonathan; LaRose, Eric; Shirzadi, Ehsan; Mahnke, Andrea; Mayer, John; Ye, Zhan; Page, David; Peissig, Peggy

2017-12-08

The study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs. The aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs. We analyzed the following two data sources: (1) biomedical articles and (2) health-related social media blog posts. We developed an intelligent and scalable text mining solution on big data infrastructures composed of Apache Spark, natural language processing, and machine learning. This was combined with an Elasticsearch No-SQL distributed database to explore and visualize ADEs. The accuracy, precision, recall, and area under receiver operating characteristic of the system were 92.7%, 93.6%, 93.0%, and 0.905, respectively, and showed better results in comparison with traditional approaches in the literature. This work not only detected and classified ADE sentences from big data biomedical literature but also scientifically visualized ADE interactions. To the best of our knowledge, this work is the first to investigate a big data machine learning strategy for ADE discovery on massive datasets downloaded from PubMed Central and social media. This contribution illustrates possible capacities in big data biomedical text analysis using advanced computational methods with real-time update from new data published on a daily basis. ©Ahmad P Tafti, Jonathan Badger, Eric LaRose, Ehsan Shirzadi, Andrea Mahnke, John Mayer, Zhan Ye, David Page, Peggy Peissig. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 08.12.2017.

Medical informatics and telemedicine: A vision

NASA Technical Reports Server (NTRS)

Clemmer, Terry P.

1991-01-01

The goal of medical informatics is to improve care. This requires the commitment and harmonious collaboration between the computer scientists and clinicians and an integrated database. The vision described is how medical information systems are going to impact the way medical care is delivered in the future.

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Accelerating Translational Research by Clinically Driven Development of an Informatics Platform–A Case Study

PubMed Central

Abugessaisa, Imad; Saevarsdottir, Saedis; Tsipras, Giorgos; Lindblad, Staffan; Sandin, Charlotta; Nikamo, Pernilla; Ståhle, Mona; Malmström, Vivianne; Klareskog, Lars; Tegnér, Jesper

2014-01-01

Translational medicine is becoming increasingly dependent upon data generated from health care, clinical research, and molecular investigations. This increasing rate of production and diversity in data has brought about several challenges, including the need to integrate fragmented databases, enable secondary use of patient clinical data from health care in clinical research, and to create information systems that clinicians and biomedical researchers can readily use. Our case study effectively integrates requirements from the clinical and biomedical researcher perspectives in a translational medicine setting. Our three principal achievements are (a) a design of a user-friendly web-based system for management and integration of clinical and molecular databases, while adhering to proper de-identification and security measures; (b) providing a real-world test of the system functionalities using clinical cohorts; and (c) system integration with a clinical decision support system to demonstrate system interoperability. We engaged two active clinical cohorts, 747 psoriasis patients and 2001 rheumatoid arthritis patients, to demonstrate efficient query possibilities across the data sources, enable cohort stratification, extract variation in antibody patterns, study biomarker predictors of treatment response in RA patients, and to explore metabolic profiles of psoriasis patients. Finally, we demonstrated system interoperability by enabling integration with an established clinical decision support system in health care. To assure the usefulness and usability of the system, we followed two approaches. First, we created a graphical user interface supporting all user interactions. Secondly we carried out a system performance evaluation study where we measured the average response time in seconds for active users, http errors, and kilobits per second received and sent. The maximum response time was found to be 0.12 seconds; no server or client errors of any kind were detected. In conclusion, the system can readily be used by clinicians and biomedical researchers in a translational medicine setting. PMID:25203647

Accelerating translational research by clinically driven development of an informatics platform--a case study.

PubMed

Abugessaisa, Imad; Saevarsdottir, Saedis; Tsipras, Giorgos; Lindblad, Staffan; Sandin, Charlotta; Nikamo, Pernilla; Ståhle, Mona; Malmström, Vivianne; Klareskog, Lars; Tegnér, Jesper

2014-01-01

Translational medicine is becoming increasingly dependent upon data generated from health care, clinical research, and molecular investigations. This increasing rate of production and diversity in data has brought about several challenges, including the need to integrate fragmented databases, enable secondary use of patient clinical data from health care in clinical research, and to create information systems that clinicians and biomedical researchers can readily use. Our case study effectively integrates requirements from the clinical and biomedical researcher perspectives in a translational medicine setting. Our three principal achievements are (a) a design of a user-friendly web-based system for management and integration of clinical and molecular databases, while adhering to proper de-identification and security measures; (b) providing a real-world test of the system functionalities using clinical cohorts; and (c) system integration with a clinical decision support system to demonstrate system interoperability. We engaged two active clinical cohorts, 747 psoriasis patients and 2001 rheumatoid arthritis patients, to demonstrate efficient query possibilities across the data sources, enable cohort stratification, extract variation in antibody patterns, study biomarker predictors of treatment response in RA patients, and to explore metabolic profiles of psoriasis patients. Finally, we demonstrated system interoperability by enabling integration with an established clinical decision support system in health care. To assure the usefulness and usability of the system, we followed two approaches. First, we created a graphical user interface supporting all user interactions. Secondly we carried out a system performance evaluation study where we measured the average response time in seconds for active users, http errors, and kilobits per second received and sent. The maximum response time was found to be 0.12 seconds; no server or client errors of any kind were detected. In conclusion, the system can readily be used by clinicians and biomedical researchers in a translational medicine setting.

Integrating text mining into the MGI biocuration workflow

PubMed Central

Dowell, K.G.; McAndrews-Hill, M.S.; Hill, D.P.; Drabkin, H.J.; Blake, J.A.

2009-01-01

A major challenge for functional and comparative genomics resource development is the extraction of data from the biomedical literature. Although text mining for biological data is an active research field, few applications have been integrated into production literature curation systems such as those of the model organism databases (MODs). Not only are most available biological natural language (bioNLP) and information retrieval and extraction solutions difficult to adapt to existing MOD curation workflows, but many also have high error rates or are unable to process documents available in those formats preferred by scientific journals. In September 2008, Mouse Genome Informatics (MGI) at The Jackson Laboratory initiated a search for dictionary-based text mining tools that we could integrate into our biocuration workflow. MGI has rigorous document triage and annotation procedures designed to identify appropriate articles about mouse genetics and genome biology. We currently screen ∼1000 journal articles a month for Gene Ontology terms, gene mapping, gene expression, phenotype data and other key biological information. Although we do not foresee that curation tasks will ever be fully automated, we are eager to implement named entity recognition (NER) tools for gene tagging that can help streamline our curation workflow and simplify gene indexing tasks within the MGI system. Gene indexing is an MGI-specific curation function that involves identifying which mouse genes are being studied in an article, then associating the appropriate gene symbols with the article reference number in the MGI database. Here, we discuss our search process, performance metrics and success criteria, and how we identified a short list of potential text mining tools for further evaluation. We provide an overview of our pilot projects with NCBO's Open Biomedical Annotator and Fraunhofer SCAI's ProMiner. In doing so, we prove the potential for the further incorporation of semi-automated processes into the curation of the biomedical literature. PMID:20157492

Integrating text mining into the MGI biocuration workflow.

PubMed

Dowell, K G; McAndrews-Hill, M S; Hill, D P; Drabkin, H J; Blake, J A

2009-01-01

A major challenge for functional and comparative genomics resource development is the extraction of data from the biomedical literature. Although text mining for biological data is an active research field, few applications have been integrated into production literature curation systems such as those of the model organism databases (MODs). Not only are most available biological natural language (bioNLP) and information retrieval and extraction solutions difficult to adapt to existing MOD curation workflows, but many also have high error rates or are unable to process documents available in those formats preferred by scientific journals.In September 2008, Mouse Genome Informatics (MGI) at The Jackson Laboratory initiated a search for dictionary-based text mining tools that we could integrate into our biocuration workflow. MGI has rigorous document triage and annotation procedures designed to identify appropriate articles about mouse genetics and genome biology. We currently screen approximately 1000 journal articles a month for Gene Ontology terms, gene mapping, gene expression, phenotype data and other key biological information. Although we do not foresee that curation tasks will ever be fully automated, we are eager to implement named entity recognition (NER) tools for gene tagging that can help streamline our curation workflow and simplify gene indexing tasks within the MGI system. Gene indexing is an MGI-specific curation function that involves identifying which mouse genes are being studied in an article, then associating the appropriate gene symbols with the article reference number in the MGI database.Here, we discuss our search process, performance metrics and success criteria, and how we identified a short list of potential text mining tools for further evaluation. We provide an overview of our pilot projects with NCBO's Open Biomedical Annotator and Fraunhofer SCAI's ProMiner. In doing so, we prove the potential for the further incorporation of semi-automated processes into the curation of the biomedical literature.

An analysis of application of health informatics in Traditional Medicine: A review of four Traditional Medicine Systems.

PubMed

Raja Ikram, Raja Rina; Abd Ghani, Mohd Khanapi; Abdullah, Noraswaliza

2015-11-01

This paper shall first investigate the informatics areas and applications of the four Traditional Medicine systems - Traditional Chinese Medicine (TCM), Ayurveda, Traditional Arabic and Islamic Medicine and Traditional Malay Medicine. Then, this paper shall examine the national informatics infrastructure initiatives in the four respective countries that support the Traditional Medicine systems. Challenges of implementing informatics in Traditional Medicine Systems shall also be discussed. The literature was sourced from four databases: Ebsco Host, IEEE Explore, Proquest and Google scholar. The search term used was "Traditional Medicine", "informatics", "informatics infrastructure", "traditional Chinese medicine", "Ayurveda", "traditional Arabic and Islamic medicine", and "traditional malay medicine". A combination of the search terms above was also executed to enhance the searching process. A search was also conducted in Google to identify miscellaneous books, publications, and organization websites using the same terms. Amongst major advancements in TCM and Ayurveda are bioinformatics, development of Traditional Medicine databases for decision system support, data mining and image processing. Traditional Chinese Medicine differentiates itself from other Traditional Medicine systems with documented ISO Standards to support the standardization of TCM. Informatics applications in Traditional Arabic and Islamic Medicine are mostly ehealth applications that focus more on spiritual healing, Islamic obligations and prophetic traditions. Literature regarding development of health informatics to support Traditional Malay Medicine is still insufficient. Major informatics infrastructure that is common in China and India are automated insurance payment systems for Traditional Medicine treatment. National informatics infrastructure in Middle East and Malaysia mainly cater for modern medicine. Other infrastructure such as telemedicine and hospital information systems focus its implementation in modern medicine or are not implemented and strategized at a national level to support Traditional Medicine. Informatics may not be able to address all the emerging areas of Traditional Medicine because the concepts in Traditional Medicine system of medicine are different from modern system, though the aim may be same, i.e., to give relief to the patient. Thus, there is a need to synthesize Traditional Medicine systems and informatics with involvements from modern system of medicine. Future research works may include filling the gaps of informatics areas and integrate national informatics infrastructure with established Traditional Medicine systems. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Nursing informatics, outcomes, and quality improvement.

PubMed

Charters, Kathleen G

2003-08-01

Nursing informatics actively supports nursing by providing standard language systems, databases, decision support, readily accessible research results, and technology assessments. Through normalized datasets spanning an entire enterprise or other large demographic, nursing informatics tools support improvement of healthcare by answering questions about patient outcomes and quality improvement on an enterprise scale, and by providing documentation for business process definition, business process engineering, and strategic planning. Nursing informatics tools provide a way for advanced practice nurses to examine their practice and the effect of their actions on patient outcomes. Analysis of patient outcomes may lead to initiatives for quality improvement. Supported by nursing informatics tools, successful advance practice nurses leverage their quality improvement initiatives against the enterprise strategic plan to gain leadership support and resources.

The Emerging Role of the Chief Research Informatics Officer in Academic Health Centers.

PubMed

Sanchez-Pinto, L Nelson; Mosa, Abu S M; Fultz-Hollis, Kate; Tachinardi, Umberto; Barnett, William K; Embi, Peter J

2017-08-16

The role of the Chief Research Informatics Officer (CRIO) is emerging in academic health centers to address the challenges clinical researchers face in the increasingly digitalized, data-intensive healthcare system. Most current CRIOs are the first officers in their institutions to hold that role. To date there is very little published information about this role and the individuals who serve it. To increase our understanding of the CRIO role, the leaders who serve it, and the factors associated with their success in their organizations. The Clinical Research Informatics Working Group of the American Medical Informatics Association (AMIA) conducted a national survey of CRIOs in the United States and convened an expert panel of CRIOs to discuss their experience during the 2016 AMIA Annual Symposium. CRIOs come from diverse academic backgrounds. Most have advance training and extensive experience in biomedical informatics but the majority have been CRIOs for less than three years. CRIOs identify funding, data governance, and advancing data analytics as their major challenges. CRIOs play an important role in helping shape the future of clinical research, innovation, and data analytics in healthcare in their organizations. They share many of the same challenges and see the same opportunities for the future of the field. Better understanding the background and experience of current CRIOs can help define and develop the role in other organizations and enhance their influence in the field of research informatics.

State-Space Analysis of Working Memory in Schizophrenia: An FBIRN Study

ERIC Educational Resources Information Center

Janoos, Firdaus; Brown, Gregory; Morocz, Istvan A.; Wells, William M., III

2013-01-01

The neural correlates of "working memory" (WM) in schizophrenia (SZ) have been extensively studied using the multisite fMRI data acquired by the Functional Biomedical Informatics Research Network (fBIRN) consortium. Although univariate and multivariate analysis methods have been variously employed to localize brain responses under differing task…

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Effects of Interdisciplinary Education on Technology-Driven Application Design

ERIC Educational Resources Information Center

Tafa, Z.; Rakocevic, G.; Mihailovic, D.; Milutinovic, V.

2011-01-01

This paper describes the structure and the underlying rationale of a new course dedicated to capability maturity model integration (CMMI)-directed design of wireless sensor networks (WSNs)-based biomedical applications that stresses: 1) engineering-, medico-engineering-, and informatics-related issues; 2) design for general- and special-purpose…

[Master course in biomedical engineering].

PubMed

Jobbágy, Akos; Benyó, Zoltán; Monos, Emil

2009-11-22

The Bologna Declaration aims at harmonizing the European higher education structure. In accordance with the Declaration, biomedical engineering will be offered as a master (MSc) course also in Hungary, from year 2009. Since 1995 biomedical engineering course has been held in cooperation of three universities: Semmelweis University, Budapest Veterinary University, and Budapest University of Technology and Economics. One of the latter's faculties, Faculty of Electrical Engineering and Informatics, has been responsible for the course. Students could start their biomedical engineering studies - usually in parallel with their first degree course - after they collected at least 180 ECTS credits. Consequently, the biomedical engineering course could have been considered as a master course even before the Bologna Declaration. Students had to collect 130 ECTS credits during the six-semester course. This is equivalent to four-semester full-time studies, because during the first three semesters the curriculum required to gain only one third of the usual ECTS credits. The paper gives a survey on the new biomedical engineering master course, briefly summing up also the subjects in the curriculum.

Applications of the pipeline environment for visual informatics and genomics computations

PubMed Central

2011-01-01

Background Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data analysis protocols. Results This paper reports on the applications of the LONI Pipeline environment to address two informatics challenges - graphical management of diverse genomics tools, and the interoperability of informatics software. Specifically, this manuscript presents the concrete details of deploying general informatics suites and individual software tools to new hardware infrastructures, the design, validation and execution of new visual analysis protocols via the Pipeline graphical interface, and integration of diverse informatics tools via the Pipeline eXtensible Markup Language syntax. We demonstrate each of these processes using several established informatics packages (e.g., miBLAST, EMBOSS, mrFAST, GWASS, MAQ, SAMtools, Bowtie) for basic local sequence alignment and search, molecular biology data analysis, and genome-wide association studies. These examples demonstrate the power of the Pipeline graphical workflow environment to enable integration of bioinformatics resources which provide a well-defined syntax for dynamic specification of the input/output parameters and the run-time execution controls. Conclusions The LONI Pipeline environment http://pipeline.loni.ucla.edu provides a flexible graphical infrastructure for efficient biomedical computing and distributed informatics research. The interactive Pipeline resource manager enables the utilization and interoperability of diverse types of informatics resources. The Pipeline client-server model provides computational power to a broad spectrum of informatics investigators - experienced developers and novice users, user with or without access to advanced computational-resources (e.g., Grid, data), as well as basic and translational scientists. The open development, validation and dissemination of computational networks (pipeline workflows) facilitates the sharing of knowledge, tools, protocols and best practices, and enables the unbiased validation and replication of scientific findings by the entire community. PMID:21791102

From bed to bench: bridging from informatics practice to theory: an exploratory analysis.

PubMed

Haux, R; Lehmann, C U

2014-01-01

In 2009, Applied Clinical Informatics (ACI)--focused on applications in clinical informatics--was launched as a companion journal to Methods of Information in Medicine (MIM). Both journals are official journals of the International Medical Informatics Association. To explore which congruencies and interdependencies exist in publications from theory to practice and from practice to theory and to determine existing gaps. Major topics discussed in ACI and MIM were analyzed. We explored if the intention of publishing companion journals to provide an information bridge from informatics theory to informatics practice and vice versa could be supported by this model. In this manuscript we will report on congruencies and interdependences from practice to theory and on major topics in MIM. Retrospective, prolective observational study on recent publications of ACI and MIM. All publications of the years 2012 and 2013 were indexed and analyzed. Hundred and ninety-six publications were analyzed (ACI 87, MIM 109). In MIM publications, modelling aspects as well as methodological and evaluation approaches for the analysis of data, information, and knowledge in biomedicine and health care were frequently raised - and often discussed from an interdisciplinary point of view. Important themes were ambient-assisted living, anatomic spatial relations, biomedical informatics as scientific discipline, boosting, coding, computerized physician order entry, data analysis, grid and cloud computing, health care systems and services, health-enabling technologies, health information search, health information systems, imaging, knowledge-based decision support, patient records, signal analysis, and web science. Congruencies between journals could be found in themes, but with a different focus on content. Interdependencies from practice to theory, found in these publications, were only limited. Bridging from informatics theory to practice and vice versa remains a major component of successful research and practice as well as a major challenge.

Informatics and Standards for Nanomedicine Technology

PubMed Central

Thomas, Dennis G.; Klaessig, Fred; Harper, Stacey L.; Fritts, Martin; Hoover, Mark D.; Gaheen, Sharon; Stokes, Todd H.; Reznik-Zellen, Rebecca; Freund, Elaine T.; Klemm, Juli D.; Paik, David S.; Baker, Nathan A.

2011-01-01

There are several issues to be addressed concerning the management and effective use of information (or data), generated from nanotechnology studies in biomedical research and medicine. These data are large in volume, diverse in content, and are beset with gaps and ambiguities in the description and characterization of nanomaterials. In this work, we have reviewed three areas of nanomedicine informatics: information resources; taxonomies, controlled vocabularies, and ontologies; and information standards. Informatics methods and standards in each of these areas are critical for enabling collaboration, data sharing, unambiguous representation and interpretation of data, semantic (meaningful) search and integration of data; and for ensuring data quality, reliability, and reproducibility. In particular, we have considered four types of information standards in this review, which are standard characterization protocols, common terminology standards, minimum information standards, and standard data communication (exchange) formats. Currently, due to gaps and ambiguities in the data, it is also difficult to apply computational methods and machine learning techniques to analyze, interpret and recognize patterns in data that are high dimensional in nature, and also to relate variations in nanomaterial properties to variations in their chemical composition, synthesis, characterization protocols, etc. Progress towards resolving the issues of information management in nanomedicine using informatics methods and standards discussed in this review will be essential to the rapidly growing field of nanomedicine informatics. PMID:21721140

Relational Databases and Biomedical Big Data.

PubMed

de Silva, N H Nisansa D

2017-01-01

In various biomedical applications that collect, handle, and manipulate data, the amounts of data tend to build up and venture into the range identified as bigdata. In such occurrences, a design decision has to be taken as to what type of database would be used to handle this data. More often than not, the default and classical solution to this in the biomedical domain according to past research is relational databases. While this used to be the norm for a long while, it is evident that there is a trend to move away from relational databases in favor of other types and paradigms of databases. However, it still has paramount importance to understand the interrelation that exists between biomedical big data and relational databases. This chapter will review the pros and cons of using relational databases to store biomedical big data that previous researches have discussed and used.

Metadata mapping and reuse in caBIG.

PubMed

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-02-05

This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG framework or other frameworks that use metadata repositories. The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG framework and potentially any framework that uses a metadata repository. This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG. This effort contributes to facilitating the development of interoperable systems within caBIG as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies.

Rembrandt: Helping Personalized Medicine Become a Reality Through Integrative Translational Research

PubMed Central

Madhavan, Subha; Zenklusen, Jean-Claude; Kotliarov, Yuri; Sahni, Himanso; Fine, Howard A.; Buetow, Kenneth

2009-01-01

Finding better therapies for the treatment of brain tumors is hampered by the lack of consistently obtained molecular data in a large sample set, and ability to integrate biomedical data from disparate sources enabling translation of therapies from bench to bedside. Hence, a critical factor in the advancement of biomedical research and clinical translation is the ease with which data can be integrated, redistributed and analyzed both within and across functional domains. Novel biomedical informatics infrastructure and tools are essential for developing individualized patient treatment based on the specific genomic signatures in each patient’s tumor. Here we present Rembrandt, Repository of Molecular BRAin Neoplasia DaTa, a cancer clinical genomics database and a web-based data mining and analysis platform aimed at facilitating discovery by connecting the dots between clinical information and genomic characterization data. To date, Rembrandt contains data generated through the Glioma Molecular Diagnostic Initiative from 874 glioma specimens comprising nearly 566 gene expression arrays, 834 copy number arrays and 13,472 clinical phenotype data points. Data can be queried and visualized for a selected gene across all data platforms or for multiple genes in a selected platform. Additionally, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-anomaly pairs to facilitate the discovery of novel biomarkers and therapeutic targets. We believe that REMBRANDT represents a prototype of how high throughput genomic and clinical data can be integrated in a way that will allow expeditious and efficient translation of laboratory discoveries to the clinic. PMID:19208739

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology

PubMed Central

Latendresse, Mario; Paley, Suzanne M.; Krummenacker, Markus; Ong, Quang D.; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M.; Caspi, Ron

2016-01-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. PMID:26454094

Reducing Friction: An Update on the NCIP Open Development Initiative - NCI BioMedical Informatics Blog

Cancer.gov

NCIP has migrated 132 repositories from the NCI subversion repository to our public NCIP GitHub channel with the goal of facilitating third party contributions to the existing code base. Within the GitHub environment, we are advocating use of the GitHub “fork and pull” model.

76 FR 1442 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-10

... Group; Macromolecular Structure and Function D Study Section. Date: February 8-9, 2011. Time: 8 a.m. to...; Biomedical Computing and Health Informatics Study Section. Date: February 8, 2011. Time: 8 a.m. to 5 p.m... Skin Sciences Integrated Review Group; Skeletal Muscle and Exercise Physiology Study Section. Date...

A Novel Multiple Choice Question Generation Strategy: Alternative Uses for Controlled Vocabulary Thesauri in Biomedical-Sciences Education.

PubMed

Lopetegui, Marcelo A; Lara, Barbara A; Yen, Po-Yin; Çatalyürek, Ümit V; Payne, Philip R O

2015-01-01

Multiple choice questions play an important role in training and evaluating biomedical science students. However, the resource intensive nature of question generation limits their open availability, reducing their contribution to evaluation purposes mainly. Although applied-knowledge questions require a complex formulation process, the creation of concrete-knowledge questions (i.e., definitions, associations) could be assisted by the use of informatics methods. We envisioned a novel and simple algorithm that exploits validated knowledge repositories and generates concrete-knowledge questions by leveraging concepts' relationships. In this manuscript we present the development and validation of a prototype which successfully produced meaningful concrete-knowledge questions, opening new applications for existing knowledge repositories, potentially benefiting students of all biomedical sciences disciplines.

k-neighborhood Decentralization: A Comprehensive Solution to Index the UMLS for Large Scale Knowledge Discovery

PubMed Central

Xiang, Yang; Lu, Kewei; James, Stephen L.; Borlawsky, Tara B.; Huang, Kun; Payne, Philip R.O.

2011-01-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. PMID:22154838

Big data management challenges in health research-a literature review.

PubMed

Wang, Xiaoming; Williams, Carolyn; Liu, Zhen Hua; Croghan, Joe

2017-08-07

Big data management for information centralization (i.e. making data of interest findable) and integration (i.e. making related data connectable) in health research is a defining challenge in biomedical informatics. While essential to create a foundation for knowledge discovery, optimized solutions to deliver high-quality and easy-to-use information resources are not thoroughly explored. In this review, we identify the gaps between current data management approaches and the need for new capacity to manage big data generated in advanced health research. Focusing on these unmet needs and well-recognized problems, we introduce state-of-the-art concepts, approaches and technologies for data management from computing academia and industry to explore improvement solutions. We explain the potential and significance of these advances for biomedical informatics. In addition, we discuss specific issues that have a great impact on technical solutions for developing the next generation of digital products (tools and data) to facilitate the raw-data-to-knowledge process in health research. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

k-Neighborhood decentralization: a comprehensive solution to index the UMLS for large scale knowledge discovery.

PubMed

Xiang, Yang; Lu, Kewei; James, Stephen L; Borlawsky, Tara B; Huang, Kun; Payne, Philip R O

2012-04-01

The Unified Medical Language System (UMLS) is the largest thesaurus in the biomedical informatics domain. Previous works have shown that knowledge constructs comprised of transitively-associated UMLS concepts are effective for discovering potentially novel biomedical hypotheses. However, the extremely large size of the UMLS becomes a major challenge for these applications. To address this problem, we designed a k-neighborhood Decentralization Labeling Scheme (kDLS) for the UMLS, and the corresponding method to effectively evaluate the kDLS indexing results. kDLS provides a comprehensive solution for indexing the UMLS for very efficient large scale knowledge discovery. We demonstrated that it is highly effective to use kDLS paths to prioritize disease-gene relations across the whole genome, with extremely high fold-enrichment values. To our knowledge, this is the first indexing scheme capable of supporting efficient large scale knowledge discovery on the UMLS as a whole. Our expectation is that kDLS will become a vital engine for retrieving information and generating hypotheses from the UMLS for future medical informatics applications. Copyright © 2011 Elsevier Inc. All rights reserved.

A new visual navigation system for exploring biomedical Open Educational Resource (OER) videos.

PubMed

Zhao, Baoquan; Xu, Songhua; Lin, Shujin; Luo, Xiaonan; Duan, Lian

2016-04-01

Biomedical videos as open educational resources (OERs) are increasingly proliferating on the Internet. Unfortunately, seeking personally valuable content from among the vast corpus of quality yet diverse OER videos is nontrivial due to limitations of today's keyword- and content-based video retrieval techniques. To address this need, this study introduces a novel visual navigation system that facilitates users' information seeking from biomedical OER videos in mass quantity by interactively offering visual and textual navigational clues that are both semantically revealing and user-friendly. The authors collected and processed around 25 000 YouTube videos, which collectively last for a total length of about 4000 h, in the broad field of biomedical sciences for our experiment. For each video, its semantic clues are first extracted automatically through computationally analyzing audio and visual signals, as well as text either accompanying or embedded in the video. These extracted clues are subsequently stored in a metadata database and indexed by a high-performance text search engine. During the online retrieval stage, the system renders video search results as dynamic web pages using a JavaScript library that allows users to interactively and intuitively explore video content both efficiently and effectively.ResultsThe authors produced a prototype implementation of the proposed system, which is publicly accessible athttps://patentq.njit.edu/oer To examine the overall advantage of the proposed system for exploring biomedical OER videos, the authors further conducted a user study of a modest scale. The study results encouragingly demonstrate the functional effectiveness and user-friendliness of the new system for facilitating information seeking from and content exploration among massive biomedical OER videos. Using the proposed tool, users can efficiently and effectively find videos of interest, precisely locate video segments delivering personally valuable information, as well as intuitively and conveniently preview essential content of a single or a collection of videos. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Informatics competencies for nurse leaders: protocol for a scoping review.

PubMed

Kassam, Iman; Nagle, Lynn; Strudwick, Gillian

2017-12-14

Globally, health information technologies are now being used by nurses in a variety of settings. However, nurse leaders often do not have the necessary strategic and tactical informatics competencies to adequately ensure their effective adoption and use. Although informatics competencies and competency frameworks have been identified and developed, to date there has not been review or consolidation of the work completed in this area. In order to address this gap, a scoping review is being conducted. The objectives of this scoping review are to: (1) identify informatics competencies of relevance to nurse leaders, (2) identify frameworks or theories that have been used to develop informatics competencies for nurse leaders, (3) identify instruments used to assess the informatics competencies of nurse leaders and (4) examine the psychometric properties of identified instruments. Using the Arksey and O'Malley five-step framework, a literature review will be conducted using a scoping review methodology. The search will encompass academic and grey literature and include two primary databases and five secondary databases. Identified studies and documents will be independently screened for eligibility by two reviewers. Data from the studies and documents will be extracted and compiled into a chart. Qualitative data will be subject to a thematic analysis and descriptive statistics applied to the quantitative data. Ethical approval was not required for this study. Results will be used to inform a future study designed to validate an instrument used to evaluate informatics competencies for nurse leaders within a Canadian context. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Architecture of a Biomedical Informatics Research Data Management Pipeline.

PubMed

Bauer, Christian R; Umbach, Nadine; Baum, Benjamin; Buckow, Karoline; Franke, Thomas; Grütz, Romanus; Gusky, Linda; Nussbeck, Sara Yasemin; Quade, Matthias; Rey, Sabine; Rottmann, Thorsten; Rienhoff, Otto; Sax, Ulrich

2016-01-01

In University Medical Centers, heterogeneous data are generated that cannot always be clearly attributed to patient care or biomedical research. Each data set has to adhere to distinct intrinsic and operational quality standards. However, only if high-quality data, tools to work with the data, and most importantly guidelines and rules of how to work with the data are addressed adequately, an infrastructure can be sustainable. Here, we present the IT Research Architecture of the University Medical Center Göttingen and describe our ten years' experience and lessons learned with infrastructures in networked medical research.

Examining the need & potential for biomedical engineering to strengthen health care delivery for displaced populations & victims of conflict.

PubMed

Nadkarni, Devika; Elhajj, Imad; Dawy, Zaher; Ghattas, Hala; Zaman, Muhammad H

2017-01-01

Conflict and the subsequent displacement of populations creates unique challenges in the delivery of quality health care to the affected population. Equitable access to quality care demands a multi-pronged strategy with a growing need, and role, for technological innovation to address these challenges. While there have been significant contributions towards alleviating the burden of conflict via data informatics and analytics, communication technology, and geographic information systems, little has been done within biomedical engineering. This article elaborates on the causes for gaps in biomedical innovation for refugee populations affected by conflict, tackles preconceived notions, takes stock of recent developments in promising technologies to address these challenges, and identifies tangible action items to create a stronger and sustainable pipeline for biomedical technological innovation to improve the health and well-being of an increasing group of vulnerable people around the world.

BioProspecting: novel marker discovery obtained by mining the bibleome.

PubMed

Elkin, Peter L; Tuttle, Mark S; Trusko, Brett E; Brown, Steven H

2009-02-05

BioProspecting is a novel approach that enabled our team to mine data related to genetic markers from the New England Journal of Medicine (NEJM) utilizing SNOMED CT and the Human Gene Onotology (HUGO). The Biomedical Informatics Research Collaborative was able to link genes and disorders using the Multi-threaded Clinical Vocabulary Server (MCVS) and natural language processing engine, whose output creates an ontology-network using the semantic encodings of the literature that is organized by these two terminologies. We identified relationships between (genes or proteins) and (diseases or drugs) as linked by metabolic functions and identified potentially novel functional relationships between, for example, genes and diseases (e.g. Article #1 ([Gene - IL27] = > {Enzyme - Dipeptidyl Carboxypeptidase 1}) and Article #2 ({Enzyme - Dipeptidyl Carboxypeptidase 1} < = [Disorder - Type II DM]) showing a metabolic link between IL27 and Type II DM). In this manuscript we describe our method for developing the database and its content as well as its potential to assist in the discovery of novel markers and drugs.

A structural informatics approach to mine kinase knowledge bases.

PubMed

Brooijmans, Natasja; Mobilio, Dominick; Walker, Gary; Nilakantan, Ramaswamy; Denny, Rajiah A; Feyfant, Eric; Diller, David; Bikker, Jack; Humblet, Christine

2010-03-01

In this paper, we describe a combination of structural informatics approaches developed to mine data extracted from existing structure knowledge bases (Protein Data Bank and the GVK database) with a focus on kinase ATP-binding site data. In contrast to existing systems that retrieve and analyze protein structures, our techniques are centered on a database of ligand-bound geometries in relation to residues lining the binding site and transparent access to ligand-based SAR data. We illustrate the systems in the context of the Abelson kinase and related inhibitor structures. 2009 Elsevier Ltd. All rights reserved.

Assessing the current state of dental informatics in saudi arabia: the new frontier.

PubMed

Al-Nasser, Lubna; Al-Ehaideb, Ali; Househ, Mowafa

2014-01-01

Dental informatics is an emerging field that has the potential to transform the dental profession. This study aims to summarize the current applications of dental informatics in Saudi Arabia and to identify the challenges facing expansion of dental informatics in the Saudi context. Search for published articles and specialized forum entries was conducted, as well as interviews with dental professionals familiar with the topic. Results indicated that digital radiography/analysis and administrative management of dental practice are the commonest applications used. Applications in Saudi dental education included: web-based learning systems, computer-based assessments and virtual technology for clinical skills' teaching. Patients' education software, electronic dental/oral health records and the potential of dental research output from electronic databases are yet to be achieved in Saudi Arabia. Challenges facing Saudi dental informatics include: lack of IT infrastructure/support, social acceptability and financial cost. Several initiatives are taken towards the research in dental informatics. Still, more investments are needed to fully achieve the potential of various application of informatics in dental education, practice and research.

The center for causal discovery of biomedical knowledge from big data.

PubMed

Cooper, Gregory F; Bahar, Ivet; Becich, Michael J; Benos, Panayiotis V; Berg, Jeremy; Espino, Jeremy U; Glymour, Clark; Jacobson, Rebecca Crowley; Kienholz, Michelle; Lee, Adrian V; Lu, Xinghua; Scheines, Richard

2015-11-01

The Big Data to Knowledge (BD2K) Center for Causal Discovery is developing and disseminating an integrated set of open source tools that support causal modeling and discovery of biomedical knowledge from large and complex biomedical datasets. The Center integrates teams of biomedical and data scientists focused on the refinement of existing and the development of new constraint-based and Bayesian algorithms based on causal Bayesian networks, the optimization of software for efficient operation in a supercomputing environment, and the testing of algorithms and software developed using real data from 3 representative driving biomedical projects: cancer driver mutations, lung disease, and the functional connectome of the human brain. Associated training activities provide both biomedical and data scientists with the knowledge and skills needed to apply and extend these tools. Collaborative activities with the BD2K Consortium further advance causal discovery tools and integrate tools and resources developed by other centers. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Craniofacial imaging informatics and technology development.

PubMed

Vannier, M W

2003-01-01

'Craniofacial imaging informatics' refers to image and related scientific data from the dentomaxillofacial complex, and application of 'informatics techniques' (derived from disciplines such as applied mathematics, computer science and statistics) to understand and organize the information associated with the data. Major trends in information technology determine the progress made in craniofacial imaging and informatics. These trends include industry consolidation, disruptive technologies, Moore's law, electronic atlases and on-line databases. Each of these trends is explained and documented, relative to their influence on craniofacial imaging. Craniofacial imaging is influenced by major trends that affect all medical imaging and related informatics applications. The introduction of cone beam craniofacial computed tomography scanners is an example of a disruptive technology entering the field. An important opportunity lies in the integration of biologic knowledge repositories with craniofacial images. The progress of craniofacial imaging will continue subject to limitations imposed by the underlying technologies, especially imaging informatics. Disruptive technologies will play a major role in the evolution of this field.

76 FR 7867 - Proposed Collection; Comment Request; Cancer Biomedical Informatics Grid® (caBIG®) Support...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-11

... proposed projects to be submitted to the Office of Management and Budget (OMB) for review and approval... Information Technology (CBIIT) launched the enterprise phase of the caBIG [supreg] initiative in early 2007... resources available through the caBIG [supreg] Enterprise Support Network (ESN), including the caBIG [supreg...

Knowledge management and informatics considerations for comparative effectiveness research: a case-driven exploration.

PubMed

Embi, Peter J; Hebert, Courtney; Gordillo, Gayle; Kelleher, Kelly; Payne, Philip R O

2013-08-01

As clinical data are increasingly collected and stored electronically, their potential use for comparative effectiveness research (CER) grows. Despite this promise, challenges face those wishing to leverage such data. In this paper we aim to enumerate some of the knowledge management and informatics issues common to such data reuse. After reviewing the current state of knowledge regarding biomedical informatics challenges and best practices related to CER, we then present 2 research projects at our institution. We analyze these and highlight several common themes and challenges related to the conduct of CER studies. Finally, we represent these emergent themes. The informatics challenges commonly encountered by those conducting CER studies include issues related to data information and knowledge management (eg, data reuse, data preparation) as well as those related to people and organizational issues (eg, sociotechnical factors and organizational factors). Examples of these are described in further detail and a formal framework for describing these findings is presented. Significant challenges face researchers attempting to use often diverse and heterogeneous datasets for CER. These challenges must be understood in order to be dealt with successfully and can often be overcome with the appropriate use of informatics best practices. Many research and policy questions remain to be answered in order to realize the full potential of the increasingly electronic clinical data available for such research.

Natural Language Processing Methods and Systems for Biomedical Ontology Learning

PubMed Central

Liu, Kaihong; Hogan, William R.; Crowley, Rebecca S.

2010-01-01

While the biomedical informatics community widely acknowledges the utility of domain ontologies, there remain many barriers to their effective use. One important requirement of domain ontologies is that they must achieve a high degree of coverage of the domain concepts and concept relationships. However, the development of these ontologies is typically a manual, time-consuming, and often error-prone process. Limited resources result in missing concepts and relationships as well as difficulty in updating the ontology as knowledge changes. Methodologies developed in the fields of natural language processing, information extraction, information retrieval and machine learning provide techniques for automating the enrichment of an ontology from free-text documents. In this article, we review existing methodologies and developed systems, and discuss how existing methods can benefit the development of biomedical ontologies. PMID:20647054

Rising Expectations: Access to Biomedical Information

PubMed Central

Lindberg, D. A. B.; Humphreys, B. L.

2008-01-01

Summary Objective To provide an overview of the expansion in public access to electronic biomedical information over the past two decades, with an emphasis on developments to which the U.S. National Library of Medicine contributed. Methods Review of the increasingly broad spectrum of web-accessible genomic data, biomedical literature, consumer health information, clinical trials data, and images. Results The amount of publicly available electronic biomedical information has increased dramatically over the past twenty years. Rising expectations regarding access to biomedical information were stimulated by the spread of the Internet, the World Wide Web, advanced searching and linking techniques. These informatics advances simplified and improved access to electronic information and reduced costs, which enabled inter-organizational collaborations to build and maintain large international information resources and also aided outreach and education efforts The demonstrated benefits of free access to electronic biomedical information encouraged the development of public policies that further increase the amount of information available. Conclusions Continuing rapid growth of publicly accessible electronic biomedical information presents tremendous opportunities and challenges, including the need to ensure uninterrupted access during disasters or emergencies and to manage digital resources so they remain available for future generations. PMID:18587496

Translational Research from an Informatics Perspective

NASA Technical Reports Server (NTRS)

Bernstam, Elmer; Meric-Bernstam, Funda; Johnson-Throop, Kathy A.; Turley, James P.; Smith, Jack W.

2007-01-01

Clinical and translational research (CTR) is an essential part of a sustainable global health system. Informatics is now recognized as an important en-abler of CTR and informaticians are increasingly called upon to help CTR efforts. The US National Institutes of Health mandated biomedical informatics activity as part of its new national CTR grant initiative, the Clinical and Translational Science Award (CTSA). Traditionally, translational re-search was defined as the translation of laboratory discoveries to patient care (bench to bedside). We argue, however, that there are many other kinds of translational research. Indeed, translational re-search requires the translation of knowledge dis-covered in one domain to another domain and is therefore an information-based activity. In this panel, we will expand upon this view of translational research and present three different examples of translation to illustrate the point: 1) bench to bedside, 2) Earth to space and 3) academia to community. We will conclude with a discussion of our local translational research efforts that draw on each of the three examples.

Nanoinformatics: a new area of research in nanomedicine

PubMed Central

Maojo, Victor; Fritts, Martin; de la Iglesia, Diana; Cachau, Raul E; Garcia-Remesal, Miguel; Mitchell, Joyce A; Kulikowski, Casimir

2012-01-01

Over a decade ago, nanotechnologists began research on applications of nanomaterials for medicine. This research has revealed a wide range of different challenges, as well as many opportunities. Some of these challenges are strongly related to informatics issues, dealing, for instance, with the management and integration of heterogeneous information, defining nomenclatures, taxonomies and classifications for various types of nanomaterials, and research on new modeling and simulation techniques for nanoparticles. Nanoinformatics has recently emerged in the USA and Europe to address these issues. In this paper, we present a review of nanoinformatics, describing its origins, the problems it addresses, areas of interest, and examples of current research initiatives and informatics resources. We suggest that nanoinformatics could accelerate research and development in nanomedicine, as has occurred in the past in other fields. For instance, biomedical informatics served as a fundamental catalyst for the Human Genome Project, and other genomic and –omics projects, as well as the translational efforts that link resulting molecular-level research to clinical problems and findings. PMID:22866003

Nanoinformatics: a new area of research in nanomedicine.

PubMed

Maojo, Victor; Fritts, Martin; de la Iglesia, Diana; Cachau, Raul E; Garcia-Remesal, Miguel; Mitchell, Joyce A; Kulikowski, Casimir

2012-01-01

Over a decade ago, nanotechnologists began research on applications of nanomaterials for medicine. This research has revealed a wide range of different challenges, as well as many opportunities. Some of these challenges are strongly related to informatics issues, dealing, for instance, with the management and integration of heterogeneous information, defining nomenclatures, taxonomies and classifications for various types of nanomaterials, and research on new modeling and simulation techniques for nanoparticles. Nanoinformatics has recently emerged in the USA and Europe to address these issues. In this paper, we present a review of nanoinformatics, describing its origins, the problems it addresses, areas of interest, and examples of current research initiatives and informatics resources. We suggest that nanoinformatics could accelerate research and development in nanomedicine, as has occurred in the past in other fields. For instance, biomedical informatics served as a fundamental catalyst for the Human Genome Project, and other genomic and -omics projects, as well as the translational efforts that link resulting molecular-level research to clinical problems and findings.

[caCORE: core architecture of bioinformation on cancer research in America].

PubMed

Gao, Qin; Zhang, Yan-lei; Xie, Zhi-yun; Zhang, Qi-peng; Hu, Zhang-zhi

2006-04-18

A critical factor in the advancement of biomedical research is the ease with which data can be integrated, redistributed and analyzed both within and across domains. This paper summarizes the Biomedical Information Core Infrastructure built by National Cancer Institute Center for Bioinformatics in America (NCICB). The main product from the Core Infrastructure is caCORE--cancer Common Ontologic Reference Environment, which is the infrastructure backbone supporting data management and application development at NCICB. The paper explains the structure and function of caCORE: (1) Enterprise Vocabulary Services (EVS). They provide controlled vocabulary, dictionary and thesaurus services, and EVS produces the NCI Thesaurus and the NCI Metathesaurus; (2) The Cancer Data Standards Repository (caDSR). It provides a metadata registry for common data elements. (3) Cancer Bioinformatics Infrastructure Objects (caBIO). They provide Java, Simple Object Access Protocol and HTTP-XML application programming interfaces. The vision for caCORE is to provide a common data management framework that will support the consistency, clarity, and comparability of biomedical research data and information. In addition to providing facilities for data management and redistribution, caCORE helps solve problems of data integration. All NCICB-developed caCORE components are distributed under open-source licenses that support unrestricted usage by both non-profit and commercial entities, and caCORE has laid the foundation for a number of scientific and clinical applications. Based on it, the paper expounds caCORE-base applications simply in several NCI projects, of which one is CMAP (Cancer Molecular Analysis Project), and the other is caBIG (Cancer Biomedical Informatics Grid). In the end, the paper also gives good prospects of caCORE, and while caCORE was born out of the needs of the cancer research community, it is intended to serve as a general resource. Cancer research has historically contributed to many areas beyond tumor biology. At the same time, the paper makes some suggestions about the study at the present time on biomedical informatics in China.

Relational Databases: A Transparent Framework for Encouraging Biology Students to Think Informatically

ERIC Educational Resources Information Center

Rice, Michael; Gladstone, William; Weir, Michael

2004-01-01

We discuss how relational databases constitute an ideal framework for representing and analyzing large-scale genomic data sets in biology. As a case study, we describe a Drosophila splice-site database that we recently developed at Wesleyan University for use in research and teaching. The database stores data about splice sites computed by a…

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology.

PubMed

Karp, Peter D; Latendresse, Mario; Paley, Suzanne M; Krummenacker, Markus; Ong, Quang D; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M; Caspi, Ron

2016-09-01

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Building the informatics infrastructure for comparative effectiveness research (CER): a review of the literature.

PubMed

Lopez, Marianne Hamilton; Holve, Erin; Sarkar, Indra Neil; Segal, Courtney

2012-07-01

Technological advances in clinical informatics have made large amounts of data accessible and potentially useful for research. As a result, a burgeoning literature addresses efforts to bridge the fields of health services research and biomedical informatics. The Electronic Data Methods Forum review examines peer-reviewed literature at the intersection of comparative effectiveness research and clinical informatics. The authors are specifically interested in characterizing this literature and identifying cross-cutting themes and gaps in the literature. A 3-step systematic literature search was conducted, including a structured search of PubMed, manual reviews of articles from selected publication lists, and manual reviews of research activities based on prospective electronic clinical data. Two thousand four hundred thirty-five citations were identified as potentially relevant. Ultimately, a full-text review was performed for 147 peer-reviewed papers. One hundred thirty-two articles were selected for inclusion in the review. Of these, 88 articles are the focus of the discussion in this paper. Three types of articles were identified, including papers that: (1) provide historical context or frameworks for using clinical informatics for research, (2) describe platforms and projects, and (3) discuss issues, challenges, and applications of natural language processing. In addition, 2 cross-cutting themes emerged: the challenges of conducting research in the absence of standardized ontologies and data collection; and unique data governance concerns related to the transfer, storage, deidentification, and access to electronic clinical data. Finally, the authors identified several current gaps on important topics such as the use of clinical informatics for cohort identification, cloud computing, and single point access to research data.

KaBOB: ontology-based semantic integration of biomedical databases.

PubMed

Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

2015-04-23

The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.

Reusable data in public health data-bases-problems encountered in Danish Children's Database.

PubMed

Høstgaard, Anna Marie; Pape-Haugaard, Louise

2012-01-01

Denmark have unique health informatics databases e.g. "The Children's Database", which since 2009 holds data on all Danish children from birth until 17 years of age. In the current set-up a number of potential sources of errors exist - both technical and human-which means that the data is flawed. This gives rise to erroneous statistics and makes the data unsuitable for research purposes. In order to make the data usable, it is necessary to develop new methods for validating the data generation process at the municipal/regional/national level. In the present ongoing research project, two research areas are combined: Public Health Informatics and Computer Science, and both ethnographic as well as system engineering research methods are used. The project is expected to generate new generic methods and knowledge about electronic data collection and transmission in different social contexts and by different social groups and thus to be of international importance, since this is sparsely documented in the Public Health Informatics perspective. This paper presents the preliminary results, which indicate that health information technology used ought to be subject for redesign, where a thorough insight into the work practices should be point of departure.

Metadata mapping and reuse in caBIG™

PubMed Central

Kunz, Isaac; Lin, Ming-Chin; Frey, Lewis

2009-01-01

Background This paper proposes that interoperability across biomedical databases can be improved by utilizing a repository of Common Data Elements (CDEs), UML model class-attributes and simple lexical algorithms to facilitate the building domain models. This is examined in the context of an existing system, the National Cancer Institute (NCI)'s cancer Biomedical Informatics Grid (caBIG™). The goal is to demonstrate the deployment of open source tools that can be used to effectively map models and enable the reuse of existing information objects and CDEs in the development of new models for translational research applications. This effort is intended to help developers reuse appropriate CDEs to enable interoperability of their systems when developing within the caBIG™ framework or other frameworks that use metadata repositories. Results The Dice (di-grams) and Dynamic algorithms are compared and both algorithms have similar performance matching UML model class-attributes to CDE class object-property pairs. With algorithms used, the baselines for automatically finding the matches are reasonable for the data models examined. It suggests that automatic mapping of UML models and CDEs is feasible within the caBIG™ framework and potentially any framework that uses a metadata repository. Conclusion This work opens up the possibility of using mapping algorithms to reduce cost and time required to map local data models to a reference data model such as those used within caBIG™. This effort contributes to facilitating the development of interoperable systems within caBIG™ as well as other metadata frameworks. Such efforts are critical to address the need to develop systems to handle enormous amounts of diverse data that can be leveraged from new biomedical methodologies. PMID:19208192

Enhancing research capacity of African institutions through social networking.

PubMed

Jimenez-Castellanos, Ana; Ramirez-Robles, Maximo; Shousha, Amany; Bagayoko, Cheick Oumar; Perrin, Caroline; Zolfo, Maria; Cuzin, Asa; Roland, Alima; Aryeetey, Richmond; Maojo, Victor

2013-01-01

Traditionally, participation of African researchers in top Biomedical Informatics (BMI) scientific journals and conferences has been scarce. Looking beyond these numbers, an educational goal should be to improve overall research and, therefore, to increase the number of scientists/authors able to produce and publish high quality research. In such scenario, we are carrying out various efforts to expand the capacities of various institutions located at four African countries - Egypt, Ghana, Cameroon and Mali - in the framework of a European Commission-funded project, AFRICA BUILD. This project is currently carrying out activities such as e-learning, collaborative development of informatics tools, mobility of researchers, various pilot projects, and others. Our main objective is to create a self-sustained South-South network of BMI developers.

Clinical microbiology informatics.

PubMed

Rhoads, Daniel D; Sintchenko, Vitali; Rauch, Carol A; Pantanowitz, Liron

2014-10-01

The clinical microbiology laboratory has responsibilities ranging from characterizing the causative agent in a patient's infection to helping detect global disease outbreaks. All of these processes are increasingly becoming partnered more intimately with informatics. Effective application of informatics tools can increase the accuracy, timeliness, and completeness of microbiology testing while decreasing the laboratory workload, which can lead to optimized laboratory workflow and decreased costs. Informatics is poised to be increasingly relevant in clinical microbiology, with the advent of total laboratory automation, complex instrument interfaces, electronic health records, clinical decision support tools, and the clinical implementation of microbial genome sequencing. This review discusses the diverse informatics aspects that are relevant to the clinical microbiology laboratory, including the following: the microbiology laboratory information system, decision support tools, expert systems, instrument interfaces, total laboratory automation, telemicrobiology, automated image analysis, nucleic acid sequence databases, electronic reporting of infectious agents to public health agencies, and disease outbreak surveillance. The breadth and utility of informatics tools used in clinical microbiology have made them indispensable to contemporary clinical and laboratory practice. Continued advances in technology and development of these informatics tools will further improve patient and public health care in the future. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Clinical Microbiology Informatics

PubMed Central

Sintchenko, Vitali; Rauch, Carol A.; Pantanowitz, Liron

2014-01-01

SUMMARY The clinical microbiology laboratory has responsibilities ranging from characterizing the causative agent in a patient's infection to helping detect global disease outbreaks. All of these processes are increasingly becoming partnered more intimately with informatics. Effective application of informatics tools can increase the accuracy, timeliness, and completeness of microbiology testing while decreasing the laboratory workload, which can lead to optimized laboratory workflow and decreased costs. Informatics is poised to be increasingly relevant in clinical microbiology, with the advent of total laboratory automation, complex instrument interfaces, electronic health records, clinical decision support tools, and the clinical implementation of microbial genome sequencing. This review discusses the diverse informatics aspects that are relevant to the clinical microbiology laboratory, including the following: the microbiology laboratory information system, decision support tools, expert systems, instrument interfaces, total laboratory automation, telemicrobiology, automated image analysis, nucleic acid sequence databases, electronic reporting of infectious agents to public health agencies, and disease outbreak surveillance. The breadth and utility of informatics tools used in clinical microbiology have made them indispensable to contemporary clinical and laboratory practice. Continued advances in technology and development of these informatics tools will further improve patient and public health care in the future. PMID:25278581

Envisioning the future of 'big data' biomedicine.

PubMed

Bui, Alex A T; Van Horn, John Darrell

2017-05-01

Through the increasing availability of more efficient data collection procedures, biomedical scientists are now confronting ever larger sets of data, often finding themselves struggling to process and interpret what they have gathered. This, while still more data continues to accumulate. This torrent of biomedical information necessitates creative thinking about how the data are being generated, how they might be best managed, analyzed, and eventually how they can be transformed into further scientific understanding for improving patient care. Recognizing this as a major challenge, the National Institutes of Health (NIH) has spearheaded the "Big Data to Knowledge" (BD2K) program - the agency's most ambitious biomedical informatics effort ever undertaken to date. In this commentary, we describe how the NIH has taken on "big data" science head-on, how a consortium of leading research centers are developing the means for handling large-scale data, and how such activities are being marshalled for the training of a new generation of biomedical data scientists. All in all, the NIH BD2K program seeks to position data science at the heart of 21 st Century biomedical research. Copyright © 2017 Elsevier Inc. All rights reserved.

BiOSS: A system for biomedical ontology selection.

PubMed

Martínez-Romero, Marcos; Vázquez-Naya, José M; Pereira, Javier; Pazos, Alejandro

2014-04-01

In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Clinical research informatics and electronic health record data.

PubMed

Richesson, R L; Horvath, M M; Rusincovitch, S A

2014-08-15

The goal of this survey is to discuss the impact of the growing availability of electronic health record (EHR) data on the evolving field of Clinical Research Informatics (CRI), which is the union of biomedical research and informatics. Major challenges for the use of EHR-derived data for research include the lack of standard methods for ensuring that data quality, completeness, and provenance are sufficient to assess the appropriateness of its use for research. Areas that need continued emphasis include methods for integrating data from heterogeneous sources, guidelines (including explicit phenotype definitions) for using these data in both pragmatic clinical trials and observational investigations, strong data governance to better understand and control quality of enterprise data, and promotion of national standards for representing and using clinical data. The use of EHR data has become a priority in CRI. Awareness of underlying clinical data collection processes will be essential in order to leverage these data for clinical research and patient care, and will require multi-disciplinary teams representing clinical research, informatics, and healthcare operations. Considerations for the use of EHR data provide a starting point for practical applications and a CRI research agenda, which will be facilitated by CRI's key role in the infrastructure of a learning healthcare system.

Clinical Research Informatics and Electronic Health Record Data

PubMed Central

Horvath, M. M.; Rusincovitch, S. A.

2014-01-01

Summary Objectives The goal of this survey is to discuss the impact of the growing availability of electronic health record (EHR) data on the evolving field of Clinical Research Informatics (CRI), which is the union of biomedical research and informatics. Results Major challenges for the use of EHR-derived data for research include the lack of standard methods for ensuring that data quality, completeness, and provenance are sufficient to assess the appropriateness of its use for research. Areas that need continued emphasis include methods for integrating data from heterogeneous sources, guidelines (including explicit phenotype definitions) for using these data in both pragmatic clinical trials and observational investigations, strong data governance to better understand and control quality of enterprise data, and promotion of national standards for representing and using clinical data. Conclusions The use of EHR data has become a priority in CRI. Awareness of underlying clinical data collection processes will be essential in order to leverage these data for clinical research and patient care, and will require multi-disciplinary teams representing clinical research, informatics, and healthcare operations. Considerations for the use of EHR data provide a starting point for practical applications and a CRI research agenda, which will be facilitated by CRI’s key role in the infrastructure of a learning healthcare system. PMID:25123746

Informatics and data quality at collaborative multicenter Breast and Colon Cancer Family Registries.

PubMed

McGarvey, Peter B; Ladwa, Sweta; Oberti, Mauricio; Dragomir, Anca Dana; Hedlund, Erin K; Tanenbaum, David Michael; Suzek, Baris E; Madhavan, Subha

2012-06-01

Quality control and harmonization of data is a vital and challenging undertaking for any successful data coordination center and a responsibility shared between the multiple sites that produce, integrate, and utilize the data. Here we describe a coordinated effort between scientists and data managers in the Cancer Family Registries to implement a data governance infrastructure consisting of both organizational and technical solutions. The technical solution uses a rule-based validation system that facilitates error detection and correction for data centers submitting data to a central informatics database. Validation rules comprise both standard checks on allowable values and a crosscheck of related database elements for logical and scientific consistency. Evaluation over a 2-year timeframe showed a significant decrease in the number of errors in the database and a concurrent increase in data consistency and accuracy.

Informatics and data quality at collaborative multicenter Breast and Colon Cancer Family Registries

PubMed Central

McGarvey, Peter B; Ladwa, Sweta; Oberti, Mauricio; Dragomir, Anca Dana; Hedlund, Erin K; Tanenbaum, David Michael; Suzek, Baris E

2012-01-01

Quality control and harmonization of data is a vital and challenging undertaking for any successful data coordination center and a responsibility shared between the multiple sites that produce, integrate, and utilize the data. Here we describe a coordinated effort between scientists and data managers in the Cancer Family Registries to implement a data governance infrastructure consisting of both organizational and technical solutions. The technical solution uses a rule-based validation system that facilitates error detection and correction for data centers submitting data to a central informatics database. Validation rules comprise both standard checks on allowable values and a crosscheck of related database elements for logical and scientific consistency. Evaluation over a 2-year timeframe showed a significant decrease in the number of errors in the database and a concurrent increase in data consistency and accuracy. PMID:22323393

The Health Information Technology Competencies Tool: Does It Translate for Nursing Informatics in the United States?

PubMed

Sipes, Carolyn; Hunter, Kathleen; McGonigle, Dee; West, Karen; Hill, Taryn; Hebda, Toni

2017-12-01

Information technology use in healthcare delivery mandates a prepared workforce. The initial Health Information Technology Competencies tool resulted from a 2-year transatlantic effort by experts from the US and European Union to identify approaches to develop skills and knowledge needed by healthcare workers. It was determined that competencies must be identified before strategies are established, resulting in a searchable database of more than 1000 competencies representing five domains, five skill levels, and more than 250 roles. Health Information Technology Competencies is available at no cost and supports role- or competency-based queries. Health Information Technology Competencies developers suggest its use for curriculum planning, job descriptions, and professional development.The Chamberlain College of Nursing informatics research team examined Health Information Technology Competencies for its possible application to our research and our curricular development, comparing it originally with the TIGER-based Assessment of Nursing Informatics Competencies and Nursing Informatics Competency Assessment of Level 3 and Level 4 tools, which examine informatics competencies at four levels of nursing practice. Additional analysis involved the 2015 Nursing Informatics: Scope and Standards of Practice. Informatics is a Health Information Technology Competencies domain, so clear delineation of nursing-informatics competencies was expected. Researchers found TIGER-based Assessment of Nursing Informatics Competencies and Nursing Informatics Competency Assessment of Level 3 and Level 4 differed from Health Information Technology Competencies 2016 in focus, definitions, ascribed competencies, and defined levels of expertise. When Health Information Technology Competencies 2017 was compared against the nursing informatics scope and standards, researchers found an increase in the number of informatics competencies but not to a significant degree. This is not surprising, given that Health Information Technology Competencies includes all healthcare workers, while the TIGER-based Assessment of Nursing Informatics Competencies and Nursing Informatics Competency Assessment of Level 3 and Level 4 tools and the American Nurses Association Nursing Informatics: Scope and Standards of Practice are nurse specific. No clear cross mapping across these tools and the standards of nursing informatics practice exists. Further examination and review are needed to translate Health Information Technology Competencies as a viable tool for nursing informatics use in the US.

Kristin Munch | NREL

Science.gov Websites

Information Management System, Materials Research Society Fall Meeting (2013) Photovoltaics Informatics scientific data management, database and data systems design, database clusters, storage systems integration , and distributed data analytics. She has used her experience in laboratory data management systems, lab

e-MIR2: a public online inventory of medical informatics resources.

PubMed

de la Calle, Guillermo; García-Remesal, Miguel; Nkumu-Mbomio, Nelida; Kulikowski, Casimir; Maojo, Victor

2012-08-02

Over the past years, the number of available informatics resources in medicine has grown exponentially. While specific inventories of such resources have already begun to be developed for Bioinformatics (BI), comparable inventories are as yet not available for the Medical Informatics (MI) field, so that locating and accessing them currently remains a difficult and time-consuming task. We have created a repository of MI resources from the scientific literature, providing free access to its contents through a web-based service. We define informatics resources as all those elements that constitute, serve to define or are used by informatics systems, ranging from architectures or development methodologies to terminologies, vocabularies, databases or tools. Relevant information describing the resources is automatically extracted from manuscripts published in top-ranked MI journals. We used a pattern matching approach to detect the resources' names and their main features. Detected resources are classified according to three different criteria: functionality, resource type and domain. To facilitate these tasks, we have built three different classification schemas by following a novel approach based on folksonomies and social tagging. We adopted the terminology most frequently used by MI researchers in their publications to create the concepts and hierarchical relationships belonging to the classification schemas. The classification algorithm identifies the categories associated with resources and annotates them accordingly. The database is then populated with this data after manual curation and validation. We have created an online repository of MI resources to assist researchers in locating and accessing the most suitable resources to perform specific tasks. The database contains 609 resources at the time of writing and is available at http://www.gib.fi.upm.es/eMIR2. We are continuing to expand the number of available resources by taking into account further publications as well as suggestions from users and resource developers.

e-MIR2: a public online inventory of medical informatics resources

PubMed Central

2012-01-01

Background Over the past years, the number of available informatics resources in medicine has grown exponentially. While specific inventories of such resources have already begun to be developed for Bioinformatics (BI), comparable inventories are as yet not available for the Medical Informatics (MI) field, so that locating and accessing them currently remains a difficult and time-consuming task. Description We have created a repository of MI resources from the scientific literature, providing free access to its contents through a web-based service. We define informatics resources as all those elements that constitute, serve to define or are used by informatics systems, ranging from architectures or development methodologies to terminologies, vocabularies, databases or tools. Relevant information describing the resources is automatically extracted from manuscripts published in top-ranked MI journals. We used a pattern matching approach to detect the resources’ names and their main features. Detected resources are classified according to three different criteria: functionality, resource type and domain. To facilitate these tasks, we have built three different classification schemas by following a novel approach based on folksonomies and social tagging. We adopted the terminology most frequently used by MI researchers in their publications to create the concepts and hierarchical relationships belonging to the classification schemas. The classification algorithm identifies the categories associated with resources and annotates them accordingly. The database is then populated with this data after manual curation and validation. Conclusions We have created an online repository of MI resources to assist researchers in locating and accessing the most suitable resources to perform specific tasks. The database contains 609 resources at the time of writing and is available at http://www.gib.fi.upm.es/eMIR2. We are continuing to expand the number of available resources by taking into account further publications as well as suggestions from users and resource developers. PMID:22857741

Consumer Health Informatics: Past, Present, and Future of a Rapidly Evolving Domain.

PubMed

Demiris, G

2016-05-20

Consumer Health Informatics (CHI) is a rapidly growing domain within the field of biomedical and health informatics. The objective of this paper is to reflect on the past twenty five years and showcase informatics concepts and applications that led to new models of care and patient empowerment, and to predict future trends and challenges for the next 25 years. We discuss concepts and systems based on a review and analysis of published literature in the consumer health informatics domain in the last 25 years. The field was introduced with the vision that one day patients will be in charge of their own health care using informatics tools and systems. Scientific literature in the field originally focused on ways to assess the quality and validity of available printed health information, only to grow significantly to cover diverse areas such as online communities, social media, and shared decision-making. Concepts such as home telehealth, mHealth, and the quantified-self movement, tools to address transparency of health care organizations, and personal health records and portals provided significant milestones in the field. Consumers are able to actively participate in the decision-making process and to engage in health care processes and decisions. However, challenges such as health literacy and the digital divide have hindered us from maximizing the potential of CHI tools with a significant portion of underserved populations unable to access and utilize them. At the same time, at a global scale consumer tools can increase access to care for underserved populations in developing countries. The field continues to grow and emerging movements such as precision medicine and the sharing economy will introduce new opportunities and challenges.

What’s Past is Prologue: A Scoping Review of Recent Public Health and Global Health Informatics Literature

PubMed Central

Dixon, Brian E.; Pina, Jamie; Kharrazi, Hadi; Gharghabi, Fardad; Richards, Janise

2015-01-01

Objective: To categorize and describe the public health informatics (PHI) and global health informatics (GHI) literature between 2012 and 2014. Methods: We conducted a semi-systematic review of articles published between January 2012 and September 2014 where information and communications technologies (ICT) was a primary subject of the study or a main component of the study methodology. Additional inclusion and exclusion criteria were used to filter PHI and GHI articles from the larger biomedical informatics domain. Articles were identified using MEDLINE as well as personal bibliographies from members of the American Medical Informatics Association PHI and GHI working groups. Results: A total of 85 PHI articles and 282 GHI articles were identified. While systems in PHI continue to support surveillance activities, we identified a shift towards support for prevention, environmental health, and public health care services. Furthermore, articles from the U.S. reveal a shift towards PHI applications at state and local levels. GHI articles focused on telemedicine, mHealth and eHealth applications. The development of adequate infrastructure to support ICT remains a challenge, although we identified a small but growing set of articles that measure the impact of ICT on clinical outcomes. Discussion: There is evidence of growth with respect to both implementation of information systems within the public health enterprise as well as a widening of scope within each informatics discipline. Yet the articles also illuminate the need for more primary research studies on what works and what does not as both searches yielded small numbers of primary, empirical articles. Conclusion: While the body of knowledge around PHI and GHI continues to mature, additional studies of higher quality are needed to generate the robust evidence base needed to support continued investment in ICT by governmental health agencies. PMID:26392846

Consumer Health Informatics: Past, Present, and Future of a Rapidly Evolving Domain

PubMed Central

2016-01-01

Summary Objectives Consumer Health Informatics (CHI) is a rapidly growing domain within the field of biomedical and health informatics. The objective of this paper is to reflect on the past twenty five years and showcase informatics concepts and applications that led to new models of care and patient empowerment, and to predict future trends and challenges for the next 25 years. Methods We discuss concepts and systems based on a review and analysis of published literature in the consumer health informatics domain in the last 25 years. Results The field was introduced with the vision that one day patients will be in charge of their own health care using informatics tools and systems. Scientific literature in the field originally focused on ways to assess the quality and validity of available printed health information, only to grow significantly to cover diverse areas such as online communities, social media, and shared decision-making. Concepts such as home telehealth, mHealth, and the quantified-self movement, tools to address transparency of health care organizations, and personal health records and portals provided significant milestones in the field. Conclusion Consumers are able to actively participate in the decision-making process and to engage in health care processes and decisions. However, challenges such as health literacy and the digital divide have hindered us from maximizing the potential of CHI tools with a significant portion of underserved populations unable to access and utilize them. At the same time, at a global scale consumer tools can increase access to care for underserved populations in developing countries. The field continues to grow and emerging movements such as precision medicine and the sharing economy will introduce new opportunities and challenges. PMID:27199196

MaizeGDB update: New tools, data, and interface for the maize model organism database

USDA-ARS?s Scientific Manuscript database

MaizeGDB is a highly curated, community-oriented database and informatics service to researchers focused on the crop plant and model organism Zea mays ssp. mays. Although some form of the maize community database has existed over the last 25 years, there have only been two major releases. In 1991, ...

Sagace: A web-based search engine for biomedical databases in Japan

PubMed Central

2012-01-01

Background In the big data era, biomedical research continues to generate a large amount of data, and the generated information is often stored in a database and made publicly available. Although combining data from multiple databases should accelerate further studies, the current number of life sciences databases is too large to grasp features and contents of each database. Findings We have developed Sagace, a web-based search engine that enables users to retrieve information from a range of biological databases (such as gene expression profiles and proteomics data) and biological resource banks (such as mouse models of disease and cell lines). With Sagace, users can search more than 300 databases in Japan. Sagace offers features tailored to biomedical research, including manually tuned ranking, a faceted navigation to refine search results, and rich snippets constructed with retrieved metadata for each database entry. Conclusions Sagace will be valuable for experts who are involved in biomedical research and drug development in both academia and industry. Sagace is freely available at http://sagace.nibio.go.jp/en/. PMID:23110816

MaizeGDB: New tools and resource

USDA-ARS?s Scientific Manuscript database

MaizeGDB, the USDA-ARS genetics and genomics database, is a highly curated, community-oriented informatics service to researchers focused on the crop plant and model organism Zea mays. MaizeGDB facilitates maize research by curating, integrating, and maintaining a database that serves as the central...

Health Information Technology as a Universal Donor to Bioethics Education.

PubMed

Goodman, Kenneth W

2017-04-01

Health information technology, sometimes called biomedical informatics, is the use of computers and networks in the health professions. This technology has become widespread, from electronic health records to decision support tools to patient access through personal health records. These computational and information-based tools have engendered their own ethics literature and now present an opportunity to shape the standard medical and nursing ethics curricula. It is suggested that each of four core components in the professional education of clinicians-privacy, end-of-life care, access to healthcare and valid consent, and clinician-patient communication-offers an opportunity to leverage health information technology for curricular improvement. Using informatics in ethics education freshens ethics pedagogy and increases its utility, and does so without additional demands on overburdened curricula.

Selling health data: de-identification, privacy, and speech.

PubMed

Kaplan, Bonnie

2015-07-01

Two court cases that involve selling prescription data for pharmaceutical marketing affect biomedical informatics, patient and clinician privacy, and regulation. Sorrell v. IMS Health Inc. et al. in the United States and R v. Department of Health, Ex Parte Source Informatics Ltd. in the United Kingdom concern privacy and health data protection, data de-identification and reidentification, drug detailing (marketing), commercial benefit from the required disclosure of personal information, clinician privacy and the duty of confidentiality, beneficial and unsavory uses of health data, regulating health technologies, and considering data as speech. Individuals should, at the very least, be aware of how data about them are collected and used. Taking account of how those data are used is needed so societal norms and law evolve ethically as new technologies affect health data privacy and protection.

Accessing and managing open medical resources in Africa over the Internet

NASA Astrophysics Data System (ADS)

Hussein, Rada; Khalifa, Aly; Jimenez-Castellanos, Ana; de la Calle, Guillermo; Ramirez-Robles, Maximo; Crespo, Jose; Perez-Rey, David; Garcia-Remesal, Miguel; Anguita, Alberto; Alonso-Calvo, Raul; de la Iglesia, Diana; Barreiro, Jose M.; Maojo, Victor

2014-10-01

Recent commentaries have proposed the advantages of using open exchange of data and informatics resources for improving health-related policies and patient care in Africa. Yet, in many African regions, both private medical and public health information systems are still unaffordable. Open exchange over the social Web 2.0 could encourage more altruistic support of medical initiatives. We have carried out some experiments to demonstrate the feasibility of using this approach to disseminate open data and informatics resources in Africa. After the experiments we developed the AFRICA BUILD Portal, the first Social Network for African biomedical researchers. Through the AFRICA BUILD Portal users can access in a transparent way to several resources. Currently, over 600 researchers are using distributed and open resources through this platform committed to low connections.

A review of causal inference for biomedical informatics

PubMed Central

Kleinberg, Samantha; Hripcsak, George

2011-01-01

Causality is an important concept throughout the health sciences and is particularly vital for informatics work such as finding adverse drug events or risk factors for disease using electronic health records. While philosophers and scientists working for centuries on formalizing what makes something a cause have not reached a consensus, new methods for inference show that we can make progress in this area in many practical cases. This article reviews core concepts in understanding and identifying causality and then reviews current computational methods for inference and explanation, focusing on inference from large-scale observational data. While the problem is not fully solved, we show that graphical models and Granger causality provide useful frameworks for inference and that a more recent approach based on temporal logic addresses some of the limitations of these methods. PMID:21782035

A medical informatics perspective on health informatics 3.0. Findings from the Yearbook 2011 section on health informatics 3.0.

PubMed

Ruch, P

2011-01-01

To summarize current advances of the so-called Web 3.0 and emerging trends of the semantic web. We provide a synopsis of the articles selected for the IMIA Yearbook 2011, from which we attempt to derive a synthetic overview of the today's and future activities in the field. while the state of the research in the field is illustrated by a set of fairly heterogeneous studies, it is possible to identify significant clusters. While the most salient challenge and obsessional target of the semantic web remains its ambition to simply interconnect all available information, it is interesting to observe the developments of complementary research fields such as information sciences and text analytics. The combined expression power and virtually unlimited data aggregation skills of Web 3.0 technologies make it a disruptive instrument to discover new biomedical knowledge. In parallel, such an unprecedented situation creates new threats for patients participating in large-scale genetic studies as Wjst demonstrate how various data set can be coupled to re-identify anonymous genetic information. The best paper selection of articles on decision support shows examples of excellent research on methods concerning original development of core semantic web techniques as well as transdisciplinary achievements as exemplified with literature-based analytics. This selected set of scientific investigations also demonstrates the needs for computerized applications to transform the biomedical data overflow into more operational clinical knowledge with potential threats for confidentiality directly associated with such advances. Altogether these papers support the idea that more elaborated computer tools, likely to combine heterogeneous text and data contents should soon emerge for the benefit of both experimentalists and hopefully clinicians.

RMS: a platform for managing cross-disciplinary and multi-institutional research project collaboration.

PubMed

Luo, Jake; Apperson-Hansen, Carolyn; Pelfrey, Clara M; Zhang, Guo-Qiang

2014-11-30

Cross-institutional cross-disciplinary collaboration has become a trend as researchers move toward building more productive and innovative teams for scientific research. Research collaboration is significantly changing the organizational structure and strategies used in the clinical and translational science domain. However, due to the obstacles of diverse administrative structures, differences in area of expertise, and communication barriers, establishing and managing a cross-institutional research project is still a challenging task. We address these challenges by creating an integrated informatics platform to reduce the barriers to biomedical research collaboration. The Request Management System (RMS) is an informatics infrastructure designed to transform a patchwork of expertise and resources into an integrated support network. The RMS facilitates investigators' initiation of new collaborative projects and supports the management of the collaboration process. In RMS, experts and their knowledge areas are categorized and managed structurally to provide consistent service. A role-based collaborative workflow is tightly integrated with domain experts and services to streamline and monitor the life-cycle of a research project. The RMS has so far tracked over 1,500 investigators with over 4,800 tasks. The research network based on the data collected in RMS illustrated that the investigators' collaborative projects increased close to 3 times from 2009 to 2012. Our experience with RMS indicates that the platform reduces barriers for cross-institutional collaboration of biomedical research projects. Building a new generation of infrastructure to enhance cross-disciplinary and multi-institutional collaboration has become an important yet challenging task. In this paper, we share the experience of developing and utilizing a collaborative project management system. The results of this study demonstrate that a web-based integrated informatics platform can facilitate and increase research interactions among investigators.

Transforming consumer health informatics through a patient work framework: connecting patients to context.

PubMed

Valdez, Rupa S; Holden, Richard J; Novak, Laurie L; Veinot, Tiffany C

2015-01-01

Designing patient-centered consumer health informatics (CHI) applications requires understanding and creating alignment with patients' and their family members' health-related activities, referred to here as 'patient work'. A patient work approach to CHI draws on medical social science and human factors engineering models and simultaneously attends to patients, their family members, activities, and context. A patient work approach extends existing approaches to CHI design that are responsive to patients' biomedical realities and personal skills and behaviors. It focuses on the embeddedness of patients' health management in larger processes and contexts and prioritizes patients' perspectives on illness management. Future research is required to advance (1) theories of patient work, (2) methods for assessing patient work, and (3) techniques for translating knowledge of patient work into CHI application design. Advancing a patient work approach within CHI is integral to developing and deploying consumer-facing technologies that are integrated with patients' everyday lives. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com. For numbered affiliations see end of article.

Presentation of the 2009 Morris F Collen Award to Betsy L Humphreys, with remarks from the recipient

PubMed Central

Ellison, Donald; Mitchell, Joyce

2010-01-01

The American College of Medical Informatics is an honorary society established to recognize those who have made sustained contributions to the field. Its highest award, for lifetime achievement and contributions to the discipline of medical informatics, is the Morris F Collen Award. Dr Collen's own efforts as a pioneer in the field stand out as the embodiment of creativity, intellectual rigor, perseverance, and personal integrity. The Collen Award, given once a year, honors an individual whose attainments have, throughout a whole career, substantially advanced the science and art of biomedical informatics. In 2009, the college was proud to present the Collen Award to Betsy Humphreys, MLS, deputy director of the National Library of Medicine. Ms Humphreys has dedicated her career to enabling more effective integration and exchange of electronic information. Her work has involved new knowledge sources and innovative strategies for advancing health data standards to accomplish these goals. Ms Humphreys becomes the first librarian to receive the Collen Award. Dr Collen, on the occasion of his 96th birthday, personally presented the award to Ms Humphreys. PMID:20595319

Building Comprehensive and Sustainable Health Informatics Institutions in Developing Countries: Moi University Experience.

PubMed

Were, Martin C; Siika, Abraham; Ayuo, Paul O; Atwoli, Lukoye; Esamai, Fabian

2015-01-01

Current approaches for capacity building in Health Informatics (HI) in developing countries mostly focus on training, and often rely on support from foreign entities. In this paper, we describe a comprehensive and multidimensional capacity-building framework by Lansang & Dennis, and its application for HI capacity building as implemented in a higher-education institution in Kenya. This framework incorporates training, learning-by-doing, partnerships, and centers of excellence. At Moi University (Kenya), the training dimensions include an accredited Masters in HI Program, PhD in HI, and HI short courses. Learning-by-doing occurs through work within MOH facilities at the AMPATH care and treatment program serving 3 million people. Moi University has formed strategic HI partnerships with Regenstrief Institute, Inc. (USA), University of Bergen (Norway), and Makerere University (Uganda), among others. The University has also created an Institute of Biomedical Informatics to serve as an HI Center of Excellence in the region. This Institute has divisions in Training, Research, Service and Administration. The HI capacity-building approach by Moi provides a model for adoption by other institutions in resource-limited settings.

Assessing information technologies for health.

PubMed

Kulikowski, C; Haux, R

2006-01-01

To provide an editorial introduction to the 2006 IMIA Yearbook of Medical Informatics with an overview of its contents and contributors. A brief overview of the main theme of 'Assessing Information Technology for Health Care', and an outline of the purposes, readership, contents, new format, and acknowledgment of contributions for the 2006 IMIA Yearbook. Assessing information technology (IT) in biomedicine and health care is emphasized in a number of survey and review articles. Synopses of a selection of best papers for the past 12 months are included, as are original papers on the history of medical informatics by pioneers in the field, and selected research and education programs. Information about IMIA and its constituent societies is given, as well as the authors, reviewers, and advisors to the Yearbook. The 2006 IMIA Yearbook of Medical Informatics highlights as its theme one of the most significant yet difficult aspects of information technology in health: the assessment of IT as part of the complex enterprise of biomedical research and practice. It is being published in a new format with a wide range of original survey and review articles.

Content Is King: Databases Preserve the Collective Information of Science.

PubMed

Yates, John R

2018-04-01

Databases store sequence information experimentally gathered to create resources that further science. In the last 20 years databases have become critical components of fields like proteomics where they provide the basis for large-scale and high-throughput proteomic informatics. Amos Bairoch, winner of the Association of Biomolecular Resource Facilities Frederick Sanger Award, has created some of the important databases proteomic research depends upon for accurate interpretation of data.

The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update

PubMed Central

Afgan, Enis; Baker, Dannon; van den Beek, Marius; Blankenberg, Daniel; Bouvier, Dave; Čech, Martin; Chilton, John; Clements, Dave; Coraor, Nate; Eberhard, Carl; Grüning, Björn; Guerler, Aysam; Hillman-Jackson, Jennifer; Von Kuster, Greg; Rasche, Eric; Soranzo, Nicola; Turaga, Nitesh; Taylor, James; Nekrutenko, Anton; Goecks, Jeremy

2016-01-01

High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale. PMID:27137889

The exploration of the exhibition informatization

NASA Astrophysics Data System (ADS)

Zhang, Jiankang

2017-06-01

The construction and management of exhibition informatization is the main task and choke point during the process of Chinese exhibition industry’s transformation and promotion. There are three key points expected to realize a breakthrough during the construction of Chinese exhibition informatization, and the three aspects respectively are adopting service outsourcing to construct and maintain the database, adopting advanced chest card technology to collect various kinds of information, developing statistics analysis to maintain good cutomer relations. The success of Chinese exhibition informatization mainly calls for mature suppliers who can provide construction and maintenance of database, the proven technology, a sense of data security, advanced chest card technology, the ability of data mining and analysis and the ability to improve the exhibition service basing on the commercial information got from the data analysis. Several data security measures are expected to apply during the process of system developing, including the measures of the terminal data security, the internet data security, the media data security, the storage data security and the application data security. The informatization of this process is based on the chest card designing. At present, there are several types of chest card technology: bar code chest card; two-dimension code card; magnetic stripe chest card; smart-chip chest card. The information got from the exhibition data will help the organizers to make relevant service strategies, quantify the accumulated indexes of the customers, and improve the level of the customer’s satisfaction and loyalty, what’s more, the information can also provide more additional services like the commercial trips, VIP ceremonial reception.

Improving the discoverability, accessibility, and citability of omics datasets: a case report.

PubMed

Darlington, Yolanda F; Naumov, Alexey; McOwiti, Apollo; Kankanamge, Wasula H; Becnel, Lauren B; McKenna, Neil J

2017-03-01

Although omics datasets represent valuable assets for hypothesis generation, model testing, and data validation, the infrastructure supporting their reuse lacks organization and consistency. Using nuclear receptor signaling transcriptomic datasets as proof of principle, we developed a model to improve the discoverability, accessibility, and citability of published omics datasets. Primary datasets were retrieved from archives, processed to extract data points, then subjected to metadata enrichment and gap filling. The resulting secondary datasets were exposed on responsive web pages to support mining of gene lists, discovery of related datasets, and single-click citation integration with popular reference managers. Automated processes were established to embed digital object identifier-driven links to the secondary datasets in associated journal articles, small molecule and gene-centric databases, and a dataset search engine. Our model creates multiple points of access to reprocessed and reannotated derivative datasets across the digital biomedical research ecosystem, promoting their visibility and usability across disparate research communities. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Life Sciences Data Archive (LSDA)

NASA Technical Reports Server (NTRS)

Fitts, M.; Johnson-Throop, Kathy; Thomas, D.; Shackelford, K.

2008-01-01

In the early days of spaceflight, space life sciences data were been collected and stored in numerous databases, formats, media-types and geographical locations. While serving the needs of individual research teams, these data were largely unknown/unavailable to the scientific community at large. As a result, the Space Act of 1958 and the Science Data Management Policy mandated that research data collected by the National Aeronautics and Space Administration be made available to the science community at large. The Biomedical Informatics and Health Care Systems Branch of the Space Life Sciences Directorate at JSC and the Data Archive Project at ARC, with funding from the Human Research Program through the Exploration Medical Capability Element, are fulfilling these requirements through the systematic population of the Life Sciences Data Archive. This program constitutes a formal system for the acquisition, archival and distribution of data for Life Sciences-sponsored experiments and investigations. The general goal of the archive is to acquire, preserve, and distribute these data using a variety of media which are accessible and responsive to inquiries from the science communities.

Medical informatics across Europe: analysis of medical informatics scientific output in 33 European countries.

PubMed

Polašek, Ozren; Kern, Josipa

2012-01-01

To investigate the medical informatics scientific output in 33 European countries. Medical Subject Heading term "medical informatics" was used to identify all relevant articles published in 1998-2007 and indexed in the Medline database. The number of articles was adjusted to the population size of each included country in order to obtain the rates per million inhabitants. A total of 28,604 articles were identified. The highest number per million inhabitants was found for Switzerland and the lowest for Albania. Overall, European Union member states had higher output than non-member states, gross domestic product was strongly associated with the scientific output in the field of medical informatics (r = 0.88, p < 0.001). While most countries had significant increase in the scientific output during the observed period, an adjustment to the European average output trend suggested that Lithuania, Portugal, Serbia and Spain had a greater increase than the rest of Europe. The results suggest large disparities across Europe. Further development of medical informatics as a profession and a clear recognition of the discipline are needed to reduce these disparities and propel further increase in research productivity.

Technical and policy approaches to balancing patient privacy and data sharing in clinical and translational research.

PubMed

Malin, Bradley; Karp, David; Scheuermann, Richard H

2010-01-01

Clinical researchers need to share data to support scientific validation and information reuse and to comply with a host of regulations and directives from funders. Various organizations are constructing informatics resources in the form of centralized databases to ensure reuse of data derived from sponsored research. The widespread use of such open databases is contingent on the protection of patient privacy. We review privacy-related problems associated with data sharing for clinical research from technical and policy perspectives. We investigate existing policies for secondary data sharing and privacy requirements in the context of data derived from research and clinical settings. In particular, we focus on policies specified by the US National Institutes of Health and the Health Insurance Portability and Accountability Act and touch on how these policies are related to current and future use of data stored in public database archives. We address aspects of data privacy and identifiability from a technical, although approachable, perspective and summarize how biomedical databanks can be exploited and seemingly anonymous records can be reidentified using various resources without hacking into secure computer systems. We highlight which clinical and translational data features, specified in emerging research models, are potentially vulnerable or exploitable. In the process, we recount a recent privacy-related concern associated with the publication of aggregate statistics from pooled genome-wide association studies that have had a significant impact on the data sharing policies of National Institutes of Health-sponsored databanks. Based on our analysis and observations we provide a list of recommendations that cover various technical, legal, and policy mechanisms that open clinical databases can adopt to strengthen data privacy protection as they move toward wider deployment and adoption.

Technical and Policy Approaches to Balancing Patient Privacy and Data Sharing in Clinical and Translational Research

PubMed Central

Malin, Bradley; Karp, David; Scheuermann, Richard H.

2010-01-01

Clinical researchers need to share data to support scientific validation and information reuse, and to comply with a host of regulations and directives from funders. Various organizations are constructing informatics resources in the form of centralized databases to ensure widespread availability of data derived from sponsored research. The widespread use of such open databases is contingent on the protection of patient privacy. In this paper, we review several aspects of the privacy-related problems associated with data sharing for clinical research from technical and policy perspectives. We begin with a review of existing policies for secondary data sharing and privacy requirements in the context of data derived from research and clinical settings. In particular, we focus on policies specified by the U.S. National Institutes of Health and the Health Insurance Portability and Accountability Act and touch upon how these policies are related to current, as well as future, use of data stored in public database archives. Next, we address aspects of data privacy and “identifiability” from a more technical perspective, and review how biomedical databanks can be exploited and seemingly anonymous records can be “re-identified” using various resources without compromising or hacking into secure computer systems. We highlight which data features specified in clinical research data models are potentially vulnerable or exploitable. In the process, we recount a recent privacy-related concern associated with the publication of aggregate statistics from pooled genome-wide association studies that has had a significant impact on the data sharing policies of NIH-sponsored databanks. Finally, we conclude with a list of recommendations that cover various technical, legal, and policy mechanisms that open clinical databases can adopt to strengthen data privacy protections as they move toward wider deployment and adoption. PMID:20051768

NIH Data Commons Pilot Phase | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The NIH, under the BD2K program, will be launching a Data Commons Pilot Phase to test ways to store, access and share Findable, Accessible, Interoperable and Reusable (FAIR) biomedical data and associated tools in the cloud. The NIH Data Commons Pilot Phase is expected to span fiscal years 2017-2020, with an estimated total budget of approximately $55.5 Million, pending available funds.

geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research.

PubMed

Glez-Peña, Daniel; Díaz, Fernando; Hernández, Jesús M; Corchado, Juan M; Fdez-Riverola, Florentino

2009-06-18

Bioinformatics and medical informatics are two research fields that serve the needs of different but related communities. Both domains share the common goal of providing new algorithms, methods and technological solutions to biomedical research, and contributing to the treatment and cure of diseases. Although different microarray techniques have been successfully used to investigate useful information for cancer diagnosis at the gene expression level, the true integration of existing methods into day-to-day clinical practice is still a long way off. Within this context, case-based reasoning emerges as a suitable paradigm specially intended for the development of biomedical informatics applications and decision support systems, given the support and collaboration involved in such a translational development. With the goals of removing barriers against multi-disciplinary collaboration and facilitating the dissemination and transfer of knowledge to real practice, case-based reasoning systems have the potential to be applied to translational research mainly because their computational reasoning paradigm is similar to the way clinicians gather, analyze and process information in their own practice of clinical medicine. In addressing the issue of bridging the existing gap between biomedical researchers and clinicians who work in the domain of cancer diagnosis, prognosis and treatment, we have developed and made accessible a common interactive framework. Our geneCBR system implements a freely available software tool that allows the use of combined techniques that can be applied to gene selection, clustering, knowledge extraction and prediction for aiding diagnosis in cancer research. For biomedical researches, geneCBR expert mode offers a core workbench for designing and testing new techniques and experiments. For pathologists or oncologists, geneCBR diagnostic mode implements an effective and reliable system that can diagnose cancer subtypes based on the analysis of microarray data using a CBR architecture. For programmers, geneCBR programming mode includes an advanced edition module for run-time modification of previous coded techniques. geneCBR is a new translational tool that can effectively support the integrative work of programmers, biomedical researches and clinicians working together in a common framework. The code is freely available under the GPL license and can be obtained at http://www.genecbr.org.

The Chicago Thoracic Oncology Database Consortium: A Multisite Database Initiative

PubMed Central

Carey, George B; Tan, Yi-Hung Carol; Bokhary, Ujala; Itkonen, Michelle; Szeto, Kyle; Wallace, James; Campbell, Nicholas; Hensing, Thomas; Salgia, Ravi

2016-01-01

Objective: An increasing amount of clinical data is available to biomedical researchers, but specifically designed database and informatics infrastructures are needed to handle this data effectively. Multiple research groups should be able to pool and share this data in an efficient manner. The Chicago Thoracic Oncology Database Consortium (CTODC) was created to standardize data collection and facilitate the pooling and sharing of data at institutions throughout Chicago and across the world. We assessed the CTODC by conducting a proof of principle investigation on lung cancer patients who took erlotinib. This study does not look into epidermal growth factor receptor (EGFR) mutations and tyrosine kinase inhibitors, but rather it discusses the development and utilization of the database involved. Methods:  We have implemented the Thoracic Oncology Program Database Project (TOPDP) Microsoft Access, the Thoracic Oncology Research Program (TORP) Velos, and the TORP REDCap databases for translational research efforts. Standard operating procedures (SOPs) were created to document the construction and proper utilization of these databases. These SOPs have been made available freely to other institutions that have implemented their own databases patterned on these SOPs. Results: A cohort of 373 lung cancer patients who took erlotinib was identified. The EGFR mutation statuses of patients were analyzed. Out of the 70 patients that were tested, 55 had mutations while 15 did not. In terms of overall survival and duration of treatment, the cohort demonstrated that EGFR-mutated patients had a longer duration of erlotinib treatment and longer overall survival compared to their EGFR wild-type counterparts who received erlotinib. Discussion: The investigation successfully yielded data from all institutions of the CTODC. While the investigation identified challenges, such as the difficulty of data transfer and potential duplication of patient data, these issues can be resolved with greater cross-communication between institutions of the consortium. Conclusion: The investigation described herein demonstrates the successful data collection from multiple institutions in the context of a collaborative effort. The data presented here can be utilized as the basis for further collaborative efforts and/or development of larger and more streamlined databases within the consortium. PMID:27092293

The Chicago Thoracic Oncology Database Consortium: A Multisite Database Initiative.

PubMed

Won, Brian; Carey, George B; Tan, Yi-Hung Carol; Bokhary, Ujala; Itkonen, Michelle; Szeto, Kyle; Wallace, James; Campbell, Nicholas; Hensing, Thomas; Salgia, Ravi

2016-03-16

An increasing amount of clinical data is available to biomedical researchers, but specifically designed database and informatics infrastructures are needed to handle this data effectively. Multiple research groups should be able to pool and share this data in an efficient manner. The Chicago Thoracic Oncology Database Consortium (CTODC) was created to standardize data collection and facilitate the pooling and sharing of data at institutions throughout Chicago and across the world. We assessed the CTODC by conducting a proof of principle investigation on lung cancer patients who took erlotinib. This study does not look into epidermal growth factor receptor (EGFR) mutations and tyrosine kinase inhibitors, but rather it discusses the development and utilization of the database involved.  We have implemented the Thoracic Oncology Program Database Project (TOPDP) Microsoft Access, the Thoracic Oncology Research Program (TORP) Velos, and the TORP REDCap databases for translational research efforts. Standard operating procedures (SOPs) were created to document the construction and proper utilization of these databases. These SOPs have been made available freely to other institutions that have implemented their own databases patterned on these SOPs. A cohort of 373 lung cancer patients who took erlotinib was identified. The EGFR mutation statuses of patients were analyzed. Out of the 70 patients that were tested, 55 had mutations while 15 did not. In terms of overall survival and duration of treatment, the cohort demonstrated that EGFR-mutated patients had a longer duration of erlotinib treatment and longer overall survival compared to their EGFR wild-type counterparts who received erlotinib. The investigation successfully yielded data from all institutions of the CTODC. While the investigation identified challenges, such as the difficulty of data transfer and potential duplication of patient data, these issues can be resolved with greater cross-communication between institutions of the consortium. The investigation described herein demonstrates the successful data collection from multiple institutions in the context of a collaborative effort. The data presented here can be utilized as the basis for further collaborative efforts and/or development of larger and more streamlined databases within the consortium.

Function Biomedical Informatics Research Network Recommendations for Prospective Multi-Center Functional Magnetic Resonance Imaging Studies

PubMed Central

Glover, Gary H.; Mueller, Bryon A.; Turner, Jessica A.; van Erp, Theo G.M.; Liu, Thomas T.; Greve, Douglas N.; Voyvodic, James T.; Rasmussen, Jerod; Brown, Gregory G.; Keator, David B.; Calhoun, Vince D.; Lee, Hyo Jong; Ford, Judith M.; Mathalon, Daniel H.; Diaz, Michele; O’Leary, Daniel S.; Gadde, Syam; Preda, Adrian; Lim, Kelvin O.; Wible, Cynthia G.; Stern, Hal S.; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G.

2011-01-01

This report provides practical recommendations for the design and execution of Multi-Center functional Magnetic Resonance Imaging (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The paper was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multi-site aspects include: (1) establishing and verifying scan parameters including scanner types and magnetic fields, (2) establishing and monitoring of a scanner quality program, (3) developing task paradigms and scan session documentation, (4) establishing clinical and scanner training to ensure consistency over time, (5) developing means for uploading, storing, and monitoring of imaging and other data, (6) the use of a traveling fMRI expert and (7) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery. PMID:22314879

Constructing the informatics and information technology foundations of a medical device evaluation system: a report from the FDA unique device identifier demonstration.

PubMed

Drozda, Joseph P; Roach, James; Forsyth, Thomas; Helmering, Paul; Dummitt, Benjamin; Tcheng, James E

2018-02-01

The US Food and Drug Administration (FDA) has recognized the need to improve the tracking of medical device safety and performance, with implementation of Unique Device Identifiers (UDIs) in electronic health information as a key strategy. The FDA funded a demonstration by Mercy Health wherein prototype UDIs were incorporated into its electronic information systems. This report describes the demonstration's informatics architecture. Prototype UDIs for coronary stents were created and implemented across a series of information systems, resulting in UDI-associated data flow from manufacture through point of use to long-term follow-up, with barcode scanning linking clinical data with UDI-associated device attributes. A reference database containing device attributes and the UDI Research and Surveillance Database (UDIR) containing the linked clinical and device information were created, enabling longitudinal assessment of device performance. The demonstration included many stakeholders: multiple Mercy departments, manufacturers, health system partners, the FDA, professional societies, the National Cardiovascular Data Registry, and information system vendors. The resulting system of systems is described in detail, including entities, functions, linkage between the UDIR and proprietary systems using UDIs as the index key, data flow, roles and responsibilities of actors, and the UDIR data model. The demonstration provided proof of concept that UDIs can be incorporated into provider and enterprise electronic information systems and used as the index key to combine device and clinical data in a database useful for device evaluation. Keys to success and challenges to achieving this goal were identified. Fundamental informatics principles were central to accomplishing the system of systems model. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Disease model curation improvements at Mouse Genome Informatics

PubMed Central

Bello, Susan M.; Richardson, Joel E.; Davis, Allan P.; Wiegers, Thomas C.; Mattingly, Carolyn J.; Dolan, Mary E.; Smith, Cynthia L.; Blake, Judith A.; Eppig, Janan T.

2012-01-01

Optimal curation of human diseases requires an ontology or structured vocabulary that contains terms familiar to end users, is robust enough to support multiple levels of annotation granularity, is limited to disease terms and is stable enough to avoid extensive reannotation following updates. At Mouse Genome Informatics (MGI), we currently use disease terms from Online Mendelian Inheritance in Man (OMIM) to curate mouse models of human disease. While OMIM provides highly detailed disease records that are familiar to many in the medical community, it lacks structure to support multilevel annotation. To improve disease annotation at MGI, we evaluated the merged Medical Subject Headings (MeSH) and OMIM disease vocabulary created by the Comparative Toxicogenomics Database (CTD) project. Overlaying MeSH onto OMIM provides hierarchical access to broad disease terms, a feature missing from the OMIM. We created an extended version of the vocabulary to meet the genetic disease-specific curation needs at MGI. Here we describe our evaluation of the CTD application, the extensions made by MGI and discuss the strengths and weaknesses of this approach. Database URL: http://www.informatics.jax.org/ PMID:22434831

The Mouse Genome Database (MGD): facilitating mouse as a model for human biology and disease.

PubMed

Eppig, Janan T; Blake, Judith A; Bult, Carol J; Kadin, James A; Richardson, Joel E

2015-01-01

The Mouse Genome Database (MGD, http://www.informatics.jax.org) serves the international biomedical research community as the central resource for integrated genomic, genetic and biological data on the laboratory mouse. To facilitate use of mouse as a model in translational studies, MGD maintains a core of high-quality curated data and integrates experimentally and computationally generated data sets. MGD maintains a unified catalog of genes and genome features, including functional RNAs, QTL and phenotypic loci. MGD curates and provides functional and phenotype annotations for mouse genes using the Gene Ontology and Mammalian Phenotype Ontology. MGD integrates phenotype data and associates mouse genotypes to human diseases, providing critical mouse-human relationships and access to repositories holding mouse models. MGD is the authoritative source of nomenclature for genes, genome features, alleles and strains following guidelines of the International Committee on Standardized Genetic Nomenclature for Mice. A new addition to MGD, the Human-Mouse: Disease Connection, allows users to explore gene-phenotype-disease relationships between human and mouse. MGD has also updated search paradigms for phenotypic allele attributes, incorporated incidental mutation data, added a module for display and exploration of genes and microRNA interactions and adopted the JBrowse genome browser. MGD resources are freely available to the scientific community. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A multimedia comprehensive informatics system with decision support tools for a multi-site collaboration research of stroke rehabilitation

NASA Astrophysics Data System (ADS)

Wang, Ximing; Documet, Jorge; Garrison, Kathleen A.; Winstein, Carolee J.; Liu, Brent

2012-02-01

Stroke is a major cause of adult disability. The Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (I-CARE) clinical trial aims to evaluate a therapy for arm rehabilitation after stroke. A primary outcome measure is correlative analysis between stroke lesion characteristics and standard measures of rehabilitation progress, from data collected at seven research facilities across the country. Sharing and communication of brain imaging and behavioral data is thus a challenge for collaboration. A solution is proposed as a web-based system with tools supporting imaging and informatics related data. In this system, users may upload anonymized brain images through a secure internet connection and the system will sort the imaging data for storage in a centralized database. Users may utilize an annotation tool to mark up images. In addition to imaging informatics, electronic data forms, for example, clinical data forms, are also integrated. Clinical information is processed and stored in the database to enable future data mining related development. Tele-consultation is facilitated through the development of a thin-client image viewing application. For convenience, the system supports access through desktop PC, laptops, and iPAD. Thus, clinicians may enter data directly into the system via iPAD while working with participants in the study. Overall, this comprehensive imaging informatics system enables users to collect, organize and analyze stroke cases efficiently.

Web impact factor: a bibliometric criterion applied to medical informatics societies' web sites.

PubMed

Soualmia, Lina Fatima; Darmoni, Stéfan Jacques; Le Duff, Franck; Douyere, Magaly; Thelwall, Maurice

2002-01-01

Several methods are available to evaluate and compare medical journals. The most popular is the journal Impact Factor, derived from averaging counts of citations to articles. Ingwersen adapted this method to assess the attractiveness of Web sites, defining the external Web Impact Factor (WIF) to be the number of external pages containing a link to a given Web site. This paper applies the WIF to 43 medical informatics societies' Web sites using advanced search engine queries to obtain the necessary link counts. The WIF was compared to the number of publications available in the Medline bibliographic database in medical informatics in these 43 countries. Between these two metrics, the observed Pearson correlation was 0.952 (p < 0.01) and the Spearman rank correlation was 0.548 (p < 0.01) showing in both cases a positive and strong significant correlation. The WIF of medicalm informatics society's Web site is statistically related to national productivity and discrepancies can be used to indicate countries where there are either weak medical informatics associations, or ones that do not make optimal use of the Web.

The integrated proactive surveillance system for prostate cancer.

PubMed

Wang, Haibin; Yatawara, Mahendra; Huang, Shao-Chi; Dudley, Kevin; Szekely, Christine; Holden, Stuart; Piantadosi, Steven

2012-01-01

In this paper, we present the design and implementation of the integrated proactive surveillance system for prostate cancer (PASS-PC). The integrated PASS-PC is a multi-institutional web-based system aimed at collecting a variety of data on prostate cancer patients in a standardized and efficient way. The integrated PASS-PC was commissioned by the Prostate Cancer Foundation (PCF) and built through the joint of efforts by a group of experts in medical oncology, genetics, pathology, nutrition, and cancer research informatics. Their main goal is facilitating the efficient and uniform collection of critical demographic, lifestyle, nutritional, dietary and clinical information to be used in developing new strategies in diagnosing, preventing and treating prostate cancer.The integrated PASS-PC is designed based on common industry standards - a three tiered architecture and a Service- Oriented Architecture (SOA). It utilizes open source software and programming languages such as HTML, PHP, CSS, JQuery, Drupal and MySQL. We also use a commercial database management system - Oracle 11g. The integrated PASS-PC project uses a "confederation model" that encourages participation of any interested center, irrespective of its size or location. The integrated PASS-PC utilizes a standardized approach to data collection and reporting, and uses extensive validation procedures to prevent entering erroneous data. The integrated PASS-PC controlled vocabulary is harmonized with the National Cancer Institute (NCI) Thesaurus. Currently, two cancer centers in the USA are participating in the integrated PASS-PC project.THE FINAL SYSTEM HAS THREE MAIN COMPONENTS: 1. National Prostate Surveillance Network (NPSN) website; 2. NPSN myConnect portal; 3. Proactive Surveillance System for Prostate Cancer (PASS-PC). PASS-PC is a cancer Biomedical Informatics Grid (caBIG) compatible product. The integrated PASS-PC provides a foundation for collaborative prostate cancer research. It has been built to meet the short term goal of gathering prostate cancer related data, but also with the prerequisites in place for future evolution into a cancer research informatics platform. In the future this will be vital for successful prostate cancer studies, care and treatment.

The Integrated Proactive Surveillance System for Prostate Cancer

PubMed Central

Wang, Haibin; Yatawara, Mahendra; Huang, Shao-Chi; Dudley, Kevin; Szekely, Christine; Holden, Stuart; Piantadosi, Steven

2012-01-01

In this paper, we present the design and implementation of the integrated proactive surveillance system for prostate cancer (PASS-PC). The integrated PASS-PC is a multi-institutional web-based system aimed at collecting a variety of data on prostate cancer patients in a standardized and efficient way. The integrated PASS-PC was commissioned by the Prostate Cancer Foundation (PCF) and built through the joint of efforts by a group of experts in medical oncology, genetics, pathology, nutrition, and cancer research informatics. Their main goal is facilitating the efficient and uniform collection of critical demographic, lifestyle, nutritional, dietary and clinical information to be used in developing new strategies in diagnosing, preventing and treating prostate cancer. The integrated PASS-PC is designed based on common industry standards – a three tiered architecture and a Service- Oriented Architecture (SOA). It utilizes open source software and programming languages such as HTML, PHP, CSS, JQuery, Drupal and MySQL. We also use a commercial database management system – Oracle 11g. The integrated PASS-PC project uses a “confederation model” that encourages participation of any interested center, irrespective of its size or location. The integrated PASS-PC utilizes a standardized approach to data collection and reporting, and uses extensive validation procedures to prevent entering erroneous data. The integrated PASS-PC controlled vocabulary is harmonized with the National Cancer Institute (NCI) Thesaurus. Currently, two cancer centers in the USA are participating in the integrated PASS-PC project. The final system has three main components: 1. National Prostate Surveillance Network (NPSN) website; 2. NPSN myConnect portal; 3. Proactive Surveillance System for Prostate Cancer (PASS-PC). PASS-PC is a cancer Biomedical Informatics Grid (caBIG) compatible product. The integrated PASS-PC provides a foundation for collaborative prostate cancer research. It has been built to meet the short term goal of gathering prostate cancer related data, but also with the prerequisites in place for future evolution into a cancer research informatics platform. In the future this will be vital for successful prostate cancer studies, care and treatment. PMID:22505956

Understanding the use of geographical information systems (GIS) in health informatics research: A review.

PubMed

Shaw, Nicola; McGuire, Suzanne

2017-06-23

The purpose of this literature review is to understand geographical information systems (GIS) and how they can be applied to public health informatics, medical informatics, and epidemiology. Relevant papers that reflected the use of geographical information systems (GIS) in health research were identified from four academic databases: Academic Search Complete, BioMed Central, PubMed Central, and Scholars Portal, as well as Google Scholar. The search strategy used was to identify articles with "geographic information systems", "GIS", "public health", "medical informatics", "epidemiology", and "health geography" as main subject headings or text words in titles and abstracts. Papers published between 1997 and 2014 were considered and a total of 39 articles were included to inform the authors on the use of GIS technologies in health informatics research. The main applications of GIS in health informatics and epidemiology include disease surveillance, health risk analysis, health access and planning, and community health profiling. GIS technologies can significantly improve quality and efficiency in health research as substantial connections can be made between a population's health and their geographical location. Gains in health informatics can be made when GIS are applied through research, however, improvements need to occur in the quantity and quality of data input for these systems to ensure better geographical health maps are used so that proper conclusions between public health and environmental factors may be made.

Bridging semantics and syntax with graph algorithms—state-of-the-art of extracting biomedical relations

PubMed Central

Uzuner, Özlem; Szolovits, Peter

2017-01-01

Research on extracting biomedical relations has received growing attention recently, with numerous biological and clinical applications including those in pharmacogenomics, clinical trial screening and adverse drug reaction detection. The ability to accurately capture both semantic and syntactic structures in text expressing these relations becomes increasingly critical to enable deep understanding of scientific papers and clinical narratives. Shared task challenges have been organized by both bioinformatics and clinical informatics communities to assess and advance the state-of-the-art research. Significant progress has been made in algorithm development and resource construction. In particular, graph-based approaches bridge semantics and syntax, often achieving the best performance in shared tasks. However, a number of problems at the frontiers of biomedical relation extraction continue to pose interesting challenges and present opportunities for great improvement and fruitful research. In this article, we place biomedical relation extraction against the backdrop of its versatile applications, present a gentle introduction to its general pipeline and shared resources, review the current state-of-the-art in methodology advancement, discuss limitations and point out several promising future directions. PMID:26851224

The Top 100 Articles in the Medical Informatics: a Bibliometric Analysis.

PubMed

Nadri, Hamed; Rahimi, Bahlol; Timpka, Toomas; Sedghi, Shahram

2017-08-19

The number of citations that a research paper receives can be used as a measure of its scientific impact. The objective of this study was to identify and to examine the characteristics of top 100 cited articles in the field of Medical Informatics based on data acquired from the Thomson Reuters' Web of Science (WOS) in October, 2016. The data was collected using two procedures: first we included articles published in the 24 journals listed in the "Medical Informatics" category; second, we retrieved articles using the key words: "informatics", "medical informatics", "biomedical informatics", "clinical informatics" and "health informatics". After removing duplicate records, articles were ranked by the number of citations they received. When the 100 top cited articles had been identified, we collected the following information for each record: all WOS database citations, year of publication, journal, author names, authors' affiliation, country of origin and topics indexed for each record. Citations for the top 100 articles ranged from 346 to 7875, and citations per year ranged from 11.12 to 525. The majority of articles were published in the 2000s (n=43) and 1990s (n=38). Articles were published across 10 journals, most commonly Statistics in medicine (n=71) and Medical decision making (n=28). The articles had an average of 2.47 authors. Statistics and biostatistics modeling was the most common topic (n=71), followed by artificial intelligence (n=12), and medical errors (n=3), other topics included data mining, diagnosis, bioinformatics, information retrieval, and medical imaging. Our bibliometric analysis illustrated a historical perspective on the progress of scientific research on Medical Informatics. Moreover, the findings of the current study provide an insight on the frequency of citations for top cited articles published in Medical Informatics as well as quality of the works, journals, and the trends steering Medical Informatics.

A centralized informatics infrastructure for the National Institute on Drug Abuse Clinical Trials Network.

PubMed

Pan, Jeng-Jong; Nahm, Meredith; Wakim, Paul; Cushing, Carol; Poole, Lori; Tai, Betty; Pieper, Carl F

2009-02-01

Clinical trial networks (CTNs) were created to provide a sustaining infrastructure for the conduct of multisite clinical trials. As such, they must withstand changes in membership. Centralization of infrastructure including knowledge management, portfolio management, information management, process automation, work policies, and procedures in clinical research networks facilitates consistency and ultimately research. In 2005, the National Institute on Drug Abuse (NIDA) CTN transitioned from a distributed data management model to a centralized informatics infrastructure to support the network's trial activities and administration. We describe the centralized informatics infrastructure and discuss our challenges to inform others considering such an endeavor. During the migration of a clinical trial network from a decentralized to a centralized data center model, descriptive data were captured and are presented here to assess the impact of centralization. We present the framework for the informatics infrastructure and evaluative metrics. The network has decreased the time from last patient-last visit to database lock from an average of 7.6 months to 2.8 months. The average database error rate decreased from 0.8% to 0.2%, with a corresponding decrease in the interquartile range from 0.04%-1.0% before centralization to 0.01-0.27% after centralization. Centralization has provided the CTN with integrated trial status reporting and the first standards-based public data share. A preliminary cost-benefit analysis showed a 50% reduction in data management cost per study participant over the life of a trial. A single clinical trial network comprising addiction researchers and community treatment programs was assessed. The findings may not be applicable to other research settings. The identified informatics components provide the information and infrastructure needed for our clinical trial network. Post centralization data management operations are more efficient and less costly, with higher data quality.

Designing high-quality interactive multimedia learning modules.

PubMed

Huang, Camillan

2005-01-01

Modern research has broadened scientific knowledge and revealed the interdisciplinary nature of the sciences. For today's students, this advance translates to learning a more diverse range of concepts, usually in less time, and without supporting resources. Students can benefit from technology-enhanced learning supplements that unify concepts and are delivered on-demand over the Internet. Such supplements, like imaging informatics databases, serve as innovative references for biomedical information, but could improve their interaction interfaces to support learning. With information from these digital datasets, multimedia learning tools can be designed to transform learning into an active process where students can visualize relationships over time, interact with dynamic content, and immediately test their knowledge. This approach bridges knowledge gaps, fosters conceptual understanding, and builds problem-solving and critical thinking skills-all essential components to informatics training for science and medicine. Additional benefits include cost-free access and ease of dissemination over the Internet or CD-ROM. However, current methods for the design of multimedia learning modules are not standardized and lack strong instructional design. Pressure from administrators at the top and students from the bottom are pushing faculty to use modern technology to address the learning needs and expectations of contemporary students. Yet, faculty lack adequate support and training to adopt this new approach. So how can faculty learn to create educational multimedia materials for their students? This paper provides guidelines on best practices in educational multimedia design, derived from the Virtual Labs Project at Stanford University. The development of a multimedia module consists of five phases: (1) understand the learning problem and the users needs; (2) design the content to harness the enabling technologies; (3) build multimedia materials with web style standards and human factors principles; (4) user testing; (5) evaluate and improve design.

Academic podcasting: quality media delivery.

PubMed

Tripp, Jacob S; Duvall, Scott L; Cowan, Derek L; Kamauu, Aaron W C

2006-01-01

A video podcast of the CME-approved University of Utah Department of Biomedical Informatics seminar was created in order to address issues with streaming video quality, take advantage of popular web-based syndication methods, and make the files available for convenient, subscription-based download. An RSS feed, which is automatically generated, contains links to the media files and allows viewers to easily subscribe to the weekly seminars in a format that guarantees consistent video quality.

Comprehensive Reproductive System Care Program - Clinical Breast Care Project (CRSCP-CBCP)

DTIC Science & Technology

2013-01-01

biomedical informatics group here, the ProLogic team, and the MDR Global leader. This Pathology Checklist tablet data capturing system development with...initiative in developing a prototype tablet application using the Pathology Checklist as the first example following a decision made at the last CBCP...enabling surgery within the center. The Breast Imaging Center has a designated Aurora Breast MRI machine. The merging of the Army and Navy Breast

Open, Cross Platform Chemistry Application Unifying Structure Manipulation, External Tools, Databases and Visualization

DTIC Science & Technology

2012-11-27

with powerful analysis tools and an informatics approach leveraging best-of-breed NoSQL databases, in order to store, search and retrieve relevant...dictionaries, and JavaScript also has good support. The MongoDB project[15] was chosen as a scalable NoSQL data store for the cheminfor- matics components

The use and misuse of biomedical data: is bigger really better?

PubMed

Hoffman, Sharona; Podgurski, Andy

2013-01-01

Very large biomedical research databases, containing electronic health records (EHR) and genomic data from millions of patients, have been heralded recently for their potential to accelerate scientific discovery and produce dramatic improvements in medical treatments. Research enabled by these databases may also lead to profound changes in law, regulation, social policy, and even litigation strategies. Yet, is "big data" necessarily better data? This paper makes an original contribution to the legal literature by focusing on what can go wrong in the process of biomedical database research and what precautions are necessary to avoid critical mistakes. We address three main reasons for approaching such research with care and being cautious in relying on its outcomes for purposes of public policy or litigation. First, the data contained in biomedical databases is surprisingly likely to be incorrect or incomplete. Second, systematic biases, arising from both the nature of the data and the preconceptions of investigators, are serious threats to the validity of research results, especially in answering causal questions. Third, data mining of biomedical databases makes it easier for individuals with political, social, or economic agendas to generate ostensibly scientific but misleading research findings for the purpose of manipulating public opinion and swaying policymakers. In short, this paper sheds much-needed light on the problems of credulous and uninformed acceptance of research results derived from biomedical databases. An understanding of the pitfalls of big data analysis is of critical importance to anyone who will rely on or dispute its outcomes, including lawyers, policymakers, and the public at large. The Article also recommends technical, methodological, and educational interventions to combat the dangers of database errors and abuses.

Practice-Based Knowledge Discovery for Comparative Effectiveness Research: An Organizing Framework

PubMed Central

Lucero, Robert J.; Bakken, Suzanne

2014-01-01

Electronic health information systems can increase the ability of health-care organizations to investigate the effects of clinical interventions. The authors present an organizing framework that integrates outcomes and informatics research paradigms to guide knowledge discovery in electronic clinical databases. They illustrate its application using the example of hospital acquired pressure ulcers (HAPU). The Knowledge Discovery through Informatics for Comparative Effectiveness Research (KDI-CER) framework was conceived as a heuristic to conceptualize study designs and address potential methodological limitations imposed by using a single research perspective. Advances in informatics research can play a complementary role in advancing the field of outcomes research including CER. The KDI-CER framework can be used to facilitate knowledge discovery from routinely collected electronic clinical data. PMID:25278645

Medical image informatics infrastructure design and applications.

PubMed

Huang, H K; Wong, S T; Pietka, E

1997-01-01

Picture archiving and communication systems (PACS) is a system integration of multimodality images and health information systems designed for improving the operation of a radiology department. As it evolves, PACS becomes a hospital image document management system with a voluminous image and related data file repository. A medical image informatics infrastructure can be designed to take advantage of existing data, providing PACS with add-on value for health care service, research, and education. A medical image informatics infrastructure (MIII) consists of the following components: medical images and associated data (including PACS database), image processing, data/knowledge base management, visualization, graphic user interface, communication networking, and application oriented software. This paper describes these components and their logical connection, and illustrates some applications based on the concept of the MIII.

The Virginia Henderson International Nursing Library: resource for nurse administrators.

PubMed

Graves, J R

1997-01-01

This article describes the major knowledge resource of the Virginia Henderson International Nursing Library, The Registry of Nursing. The first part of this article examines informatics issues and is accompanied by examples of retrieval from a typical bibliographic database and a retrieval from the Registry of Nursing Research using case mix, both as a subject heading and as a research variable. The second part of the article examines the interaction of informatics and technology used in the Registry and presents some other Library resources.

10 years experience with pioneering open access publishing in health informatics: the Journal of Medical Internet Research (JMIR).

PubMed

Eysenbach, Gunther

2010-01-01

Peer-reviewed journals remain important vehicles for knowledge transfer and dissemination in health informatics, yet, their format, processes and business models are changing only slowly. Up to the end of last century, it was common for individual researchers and scientific organizations to leave the business of knowledge transfer to professional publishers, signing away their rights to the works in the process, which in turn impeded wider dissemination. Traditional medical informatics journals are poorly cited and the visibility and uptake of articles beyond the medical informatics community remain limited. In 1999, the Journal of Medical Internet Research (JMIR; http://www.jmir.org) was launched, featuring several innovations including 1) ownership and copyright retained by the authors, 2) electronic-only, "lean" non-for-profit publishing, 3) openly accessible articles with a reversed business model (author pays instead of reader pays), 4) technological innovations such as automatic XML tagging and reference checking, on-the-fly PDF generation from XML, etc., enabling wide distribution in various bibliographic and full-text databases. In the past 10 years, despite limited resources, the journal has emerged as a leading journal in health informatics, and is presently ranked the top journal in the medical informatics and health services research categories by impact factor. The paper summarizes some of the features of the Journal, and uses bibliometric and access data to compare the influence of the Journal on the discipline of medical informatics and other disciplines. While traditional medical informatics journals are primarily cited by other Medical Informatics journals (33%-46% of citations), JMIR papers are to a more often cited by "end-users" (policy, public health, clinical journals), which may be partly attributable to the "open access advantage".

The development of large-scale de-identified biomedical databases in the age of genomics-principles and challenges.

PubMed

Dankar, Fida K; Ptitsyn, Andrey; Dankar, Samar K

2018-04-10

Contemporary biomedical databases include a wide range of information types from various observational and instrumental sources. Among the most important features that unite biomedical databases across the field are high volume of information and high potential to cause damage through data corruption, loss of performance, and loss of patient privacy. Thus, issues of data governance and privacy protection are essential for the construction of data depositories for biomedical research and healthcare. In this paper, we discuss various challenges of data governance in the context of population genome projects. The various challenges along with best practices and current research efforts are discussed through the steps of data collection, storage, sharing, analysis, and knowledge dissemination.

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database

PubMed Central

Drabkin, Harold J.; Blake, Judith A.

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as ‘GO’ or ‘homology’ or ‘phenotype’. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as ‘papers selected for GO that refer to genes with NO GO annotation’. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications. PMID:23110975

Manual Gene Ontology annotation workflow at the Mouse Genome Informatics Database.

PubMed

Drabkin, Harold J; Blake, Judith A

2012-01-01

The Mouse Genome Database, the Gene Expression Database and the Mouse Tumor Biology database are integrated components of the Mouse Genome Informatics (MGI) resource (http://www.informatics.jax.org). The MGI system presents both a consensus view and an experimental view of the knowledge concerning the genetics and genomics of the laboratory mouse. From genotype to phenotype, this information resource integrates information about genes, sequences, maps, expression analyses, alleles, strains and mutant phenotypes. Comparative mammalian data are also presented particularly in regards to the use of the mouse as a model for the investigation of molecular and genetic components of human diseases. These data are collected from literature curation as well as downloads of large datasets (SwissProt, LocusLink, etc.). MGI is one of the founding members of the Gene Ontology (GO) and uses the GO for functional annotation of genes. Here, we discuss the workflow associated with manual GO annotation at MGI, from literature collection to display of the annotations. Peer-reviewed literature is collected mostly from a set of journals available electronically. Selected articles are entered into a master bibliography and indexed to one of eight areas of interest such as 'GO' or 'homology' or 'phenotype'. Each article is then either indexed to a gene already contained in the database or funneled through a separate nomenclature database to add genes. The master bibliography and associated indexing provide information for various curator-reports such as 'papers selected for GO that refer to genes with NO GO annotation'. Once indexed, curators who have expertise in appropriate disciplines enter pertinent information. MGI makes use of several controlled vocabularies that ensure uniform data encoding, enable robust analysis and support the construction of complex queries. These vocabularies range from pick-lists to structured vocabularies such as the GO. All data associations are supported with statements of evidence as well as access to source publications.

Things to come: postmodern digital knowledge management and medical informatics.

PubMed

Matheson, N W

1995-01-01

The overarching informatics grand challenge facing society is the creation of knowledge management systems that can acquire, conserve, organize, retrieve, display, and distribute what is known today in a manner that informs and educates, facilitates the discovery and creation of new knowledge, and contributes to the health and welfare of the planet. At one time the private, national, and university libraries of the world collectively constituted the memory of society's intellectual history. In the future, these new digital knowledge management systems will constitute human memory in its entirety. The current model of multiple local collections of duplicated resources will give way to specialized sole-source servers. In this new environment all scholarly scientific knowledge should be public domain knowledge: managed by scientists, organized for the advancement of knowledge, and readily available to all. Over the next decade, the challenge for the field of medical informatics and for the libraries that serve as the continuous memory for the biomedical sciences will be to come together to form a new organization that will lead to the development of postmodern digital knowledge management systems for medicine. These systems will form a portion of the evolving world brain of the 21st century.

Collaboration leads to enhanced curriculum.

PubMed

Valerius, J; Mohan, V; Doctor, D; Hersh, W

2015-01-01

In 2007, we initiated a health information management (HIM) track of our biomedical informatics graduate program, and subsequent ongoing program assessment revealed a confluence of topics and courses within HIM and clinical informatics (CI) tracks. We completed a thorough comparative analysis of competencies derived from AMIA, AHIMA, and CAHIIM. Coupled with the need to streamline course offerings, the process, described in this paper allowed new opportunities for faculty collaboration, resulted in the creation of a model assessment for best practice in courses, and led to new avenues of growth within the program. The objective of the case study is to provide others in the informatics educational community with a model for analysis of curriculum in order to improve quality of student learning. We describe a case study where an academic informatics program realigned its course offerings to better reflect the HIM of today, and prepare for challenges of the future. Visionary leadership, intra-departmental self-analysis and alignment of the curriculum through defined mapping process reduced overlap within the CI and HIM tracks. Teaching within courses was optimized through the work of core faculty collaboration. The analysis of curriculum resulted in reduction of overlap within course curriculum. This allowed for additional and new course content to be added to existing courses. Leadership fostered an environment where top-down as well as bottom-up collaborative assessment activities resulted in a model to consolidate learning and reduce unnecessary duplication within courses. A focus on curriculum integration, emphasis on course alignment and strategic consolidation of course content raised the quality of informatics education provided to students. Faculty synergy was an essential component of this redesign process. Continuous quality improvement strategy included an ongoing alignment of curriculum and competencies through a comparative analysis approach. Through these efforts, new innovation was possible.

People and ideas in medical informatics - a half century review.

PubMed

van Bemmel, J H

2011-01-01

OBJECTIVE. Reviewing the onset and the rapid changes to make realistic predictions on the future of medical informatics. METHODS. Pointing to the contributions of the early pioneers, who had their roots in other disciplines and by illustrating that from the onset an interdisciplinary approach was characteristic for our field. RESULTS. Some of the reasons for the changes in medical informatics are that nobody was able to predict the advent of the personal computer in the 1970s, the world-wide web in 1991, and the public start of the Internet in 1992, but foremost that nobody expected that it was not primarily the hardware or the software, but human factors that would be crucial for successful applications of computers in health care. In the past sometimes unrealistic expectations were held, such as on the impact of medical decision-support systems, or on the overly optimistic contributions of electronic health records. Although the technology is widely available, some applications appear to be far more complex than expected. Health care processes can seldom be fully standardized. Humans enter at least in two very different roles in the loop of information processing: as subjects conducting care - the clinicians - and as subjects that are the objects of care - the patients. CONCLUSIONS. Medical informatics lacks a specific methodology; methods are borrowed from adjacent disciplines such as physics, mathematics and, of course, computer science. Human factors play a major role in applying computers in health care. Everyone pursuing a career in biomedical informatics needs to be very aware of this. It is to be expected that the quality of health care will increasingly be assessed by computer systems to fulfill the requirements of medical evidence.

Design and evaluation of an imaging informatics system for analytics-based decision support in radiation therapy

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; DeMarco, John; Liu, Brent J.

2015-03-01

We have developed a comprehensive DICOM RT specific database of retrospective treatment planning data for radiation therapy of head and neck cancer. Further, we have designed and built an imaging informatics module that utilizes this database to perform data mining. The end-goal of this data mining system is to provide radiation therapy decision support for incoming head and neck cancer patients, by identifying best practices from previous patients who had the most similar tumor geometries. Since the performance of such systems often depends on the size and quality of the retrospective database, we have also placed an emphasis on developing infrastructure and strategies to encourage data sharing and participation from multiple institutions. The infrastructure and decision support algorithm have both been tested and evaluated with 51 sets of retrospective treatment planning data of head and neck cancer patients. We will present the overall design and architecture of our system, an overview of our decision support mechanism as well as the results of our evaluation.

Geo-spatial Service and Application based on National E-government Network Platform and Cloud

NASA Astrophysics Data System (ADS)

Meng, X.; Deng, Y.; Li, H.; Yao, L.; Shi, J.

2014-04-01

With the acceleration of China's informatization process, our party and government take a substantive stride in advancing development and application of digital technology, which promotes the evolution of e-government and its informatization. Meanwhile, as a service mode based on innovative resources, cloud computing may connect huge pools together to provide a variety of IT services, and has become one relatively mature technical pattern with further studies and massive practical applications. Based on cloud computing technology and national e-government network platform, "National Natural Resources and Geospatial Database (NRGD)" project integrated and transformed natural resources and geospatial information dispersed in various sectors and regions, established logically unified and physically dispersed fundamental database and developed national integrated information database system supporting main e-government applications. Cross-sector e-government applications and services are realized to provide long-term, stable and standardized natural resources and geospatial fundamental information products and services for national egovernment and public users.

Transforming consumer health informatics through a patient work framework: connecting patients to context

PubMed Central

Valdez, Rupa S; Holden, Richard J; Novak, Laurie L; Veinot, Tiffany C

2015-01-01

Designing patient-centered consumer health informatics (CHI) applications requires understanding and creating alignment with patients’ and their family members’ health-related activities, referred to here as ‘patient work’. A patient work approach to CHI draws on medical social science and human factors engineering models and simultaneously attends to patients, their family members, activities, and context. A patient work approach extends existing approaches to CHI design that are responsive to patients’ biomedical realities and personal skills and behaviors. It focuses on the embeddedness of patients’ health management in larger processes and contexts and prioritizes patients’ perspectives on illness management. Future research is required to advance (1) theories of patient work, (2) methods for assessing patient work, and (3) techniques for translating knowledge of patient work into CHI application design. Advancing a patient work approach within CHI is integral to developing and deploying consumer-facing technologies that are integrated with patients’ everyday lives. PMID:25125685

NanoParticle Ontology for Cancer Nanotechnology Research

PubMed Central

Thomas, Dennis G.; Pappu, Rohit V.; Baker, Nathan A.

2010-01-01

Data generated from cancer nanotechnology research are so diverse and large in volume that it is difficult to share and efficiently use them without informatics tools. In particular, ontologies that provide a unifying knowledge framework for annotating the data are required to facilitate the semantic integration, knowledge-based searching, unambiguous interpretation, mining and inferencing of the data using informatics methods. In this paper, we discuss the design and development of NanoParticle Ontology (NPO), which is developed within the framework of the Basic Formal Ontology (BFO), and implemented in the Ontology Web Language (OWL) using well-defined ontology design principles. The NPO was developed to represent knowledge underlying the preparation, chemical composition, and characterization of nanomaterials involved in cancer research. Public releases of the NPO are available through BioPortal website, maintained by the National Center for Biomedical Ontology. Mechanisms for editorial and governance processes are being developed for the maintenance, review, and growth of the NPO. PMID:20211274

Synergies and Distinctions between Computational Disciplines in Biomedical Research: Perspective from the Clinical and Translational Science Award Programs

PubMed Central

Bernstam, Elmer V.; Hersh, William R.; Johnson, Stephen B.; Chute, Christopher G.; Nguyen, Hien; Sim, Ida; Nahm, Meredith; Weiner, Mark; Miller, Perry; DiLaura, Robert P.; Overcash, Marc; Lehmann, Harold P.; Eichmann, David; Athey, Brian D.; Scheuermann, Richard H.; Anderson, Nick; Starren, Justin B.; Harris, Paul A.; Smith, Jack W.; Barbour, Ed; Silverstein, Jonathan C.; Krusch, David A.; Nagarajan, Rakesh; Becich, Michael J.

2010-01-01

Clinical and translational research increasingly requires computation. Projects may involve multiple computationally-oriented groups including information technology (IT) professionals, computer scientists and biomedical informaticians. However, many biomedical researchers are not aware of the distinctions among these complementary groups, leading to confusion, delays and sub-optimal results. Although written from the perspective of clinical and translational science award (CTSA) programs within academic medical centers, the paper addresses issues that extend beyond clinical and translational research. The authors describe the complementary but distinct roles of operational IT, research IT, computer science and biomedical informatics using a clinical data warehouse as a running example. In general, IT professionals focus on technology. The authors distinguish between two types of IT groups within academic medical centers: central or administrative IT (supporting the administrative computing needs of large organizations) and research IT (supporting the computing needs of researchers). Computer scientists focus on general issues of computation such as designing faster computers or more efficient algorithms, rather than specific applications. In contrast, informaticians are concerned with data, information and knowledge. Biomedical informaticians draw on a variety of tools, including but not limited to computers, to solve information problems in health care and biomedicine. The paper concludes with recommendations regarding administrative structures that can help to maximize the benefit of computation to biomedical research within academic health centers. PMID:19550198

Resolving Complex Research Data Management Issues in Biomedical Laboratories: Qualitative Study of an Industry-Academia Collaboration

PubMed Central

Myneni, Sahiti; Patel, Vimla L.; Bova, G. Steven; Wang, Jian; Ackerman, Christopher F.; Berlinicke, Cynthia A.; Chen, Steve H.; Lindvall, Mikael; Zack, Donald J.

2016-01-01

This paper describes a distributed collaborative effort between industry and academia to systematize data management in an academic biomedical laboratory. Heterogeneous and voluminous nature of research data created in biomedical laboratories make information management difficult and research unproductive. One such collaborative effort was evaluated over a period of four years using data collection methods including ethnographic observations, semi-structured interviews, web-based surveys, progress reports, conference call summaries, and face-to-face group discussions. Data were analyzed using qualitative methods of data analysis to 1) characterize specific problems faced by biomedical researchers with traditional information management practices, 2) identify intervention areas to introduce a new research information management system called Labmatrix, and finally to 3) evaluate and delineate important general collaboration (intervention) characteristics that can optimize outcomes of an implementation process in biomedical laboratories. Results emphasize the importance of end user perseverance, human-centric interoperability evaluation, and demonstration of return on investment of effort and time of laboratory members and industry personnel for success of implementation process. In addition, there is an intrinsic learning component associated with the implementation process of an information management system. Technology transfer experience in a complex environment such as the biomedical laboratory can be eased with use of information systems that support human and cognitive interoperability. Such informatics features can also contribute to successful collaboration and hopefully to scientific productivity. PMID:26652980

Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics

PubMed Central

Huang, Jingshan; Dou, Dejing; Dang, Jiangbo; Pardue, J Harold; Qin, Xiao; Huan, Jun; Gerthoffer, William T; Tan, Ming

2012-01-01

Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research. PMID:22371823

MO-C-BRCD-03: The Role of Informatics in Medical Physics and Vice Versa.

PubMed

Andriole, K

2012-06-01

Like Medical Physics, Imaging Informatics encompasses concepts touching every aspect of the imaging chain from image creation, acquisition, management and archival, to image processing, analysis, display and interpretation. The two disciplines are in fact quite complementary, with similar goals to improve the quality of care provided to patients using an evidence-based approach, to assure safety in the clinical and research environments, to facilitate efficiency in the workplace, and to accelerate knowledge discovery. Use-cases describing several areas of informatics activity will be given to illustrate current limitations that would benefit from medical physicist participation, and conversely areas in which informaticists may contribute to the solution. Topics to be discussed include radiation dose monitoring, process management and quality control, display technologies, business analytics techniques, and quantitative imaging. Quantitative imaging is increasingly becoming an essential part of biomedicalresearch as well as being incorporated into clinical diagnostic activities. Referring clinicians are asking for more objective information to be gleaned from the imaging tests that they order so that they may make the best clinical management decisions for their patients. Medical Physicists may be called upon to identify existing issues as well as develop, validate and implement new approaches and technologies to help move the field further toward quantitative imaging methods for the future. Biomedical imaging informatics tools and techniques such as standards, integration, data mining, cloud computing and new systems architectures, ontologies and lexicons, data visualization and navigation tools, and business analytics applications can be used to overcome some of the existing limitations. 1. Describe what is meant by Medical Imaging Informatics and understand why the medical physicist should care. 2. Identify existing limitations in information technologies with respect to Medical Physics, and conversely see how Informatics may assist the medical physicist in filling some of the current gaps in their activities. 3. Understand general informatics concepts and areas of investigation including imaging and workflow standards, systems integration, computing architectures, ontologies, data mining and business analytics, data visualization and human-computer interface tools, and the importance of quantitative imaging for the future of Medical Physics and Imaging Informatics. 4. Become familiar with on-going efforts to address current challenges facing future research into and clinical implementation of quantitative imaging applications. © 2012 American Association of Physicists in Medicine.

MIMI: multimodality, multiresource, information integration environment for biomedical core facilities.

PubMed

Szymanski, Jacek; Wilson, David L; Zhang, Guo-Qiang

2009-10-01

The rapid expansion of biomedical research has brought substantial scientific and administrative data management challenges to modern core facilities. Scientifically, a core facility must be able to manage experimental workflow and the corresponding set of large and complex scientific data. It must also disseminate experimental data to relevant researchers in a secure and expedient manner that facilitates collaboration and provides support for data interpretation and analysis. Administratively, a core facility must be able to manage the scheduling of its equipment and to maintain a flexible and effective billing system to track material, resource, and personnel costs and charge for services to sustain its operation. It must also have the ability to regularly monitor the usage and performance of its equipment and to provide summary statistics on resources spent on different categories of research. To address these informatics challenges, we introduce a comprehensive system called MIMI (multimodality, multiresource, information integration environment) that integrates the administrative and scientific support of a core facility into a single web-based environment. We report the design, development, and deployment experience of a baseline MIMI system at an imaging core facility and discuss the general applicability of such a system in other types of core facilities. These initial results suggest that MIMI will be a unique, cost-effective approach to addressing the informatics infrastructure needs of core facilities and similar research laboratories.

The Structure of Medical Informatics Journal Literature

PubMed Central

Morris, Theodore A.; McCain, Katherine W.

1998-01-01

Abstract Objective: Medical informatics is an emergent interdisciplinary field described as drawing upon and contributing to both the health sciences and information sciences. The authors elucidate the disciplinary nature and internal structure of the field. Design: To better understand the field's disciplinary nature, the authors examine the intercitation relationships of its journal literature. To determine its internal structure, they examined its journal cocitation patterns. Measurements: The authors used data from the Science Citation Index (SCI) and Social Science Citation Index (SSCI) to perform intercitation studies among productive journal titles, and software routines from SPSS to perform multivariate data analyses on cocitation data for proposed core journals. Results: Intercitation network analysis suggests that a core literature exists, one mark of a separate discipline. Multivariate analyses of cocitation data suggest that major focus areas within the field include biomedical engineering, biomedical computing, decision support, and education. The interpretable dimensions of multidimensional scaling maps differed for the SCI and SSCI data sets. Strong links to information science literature were not found. Conclusion: The authors saw indications of a core literature and of several major research fronts. The field appears to be viewed differently by authors writing in journals indexed by SCI from those writing in journals indexed by SSCI, with more emphasis placed on computers and engineering versus decision making by the former and more emphasis on theory versus application (clinical practice) by the latter. PMID:9760393

Epilepsy informatics and an ontology-driven infrastructure for large database research and patient care in epilepsy.

PubMed

Sahoo, Satya S; Zhang, Guo-Qiang; Lhatoo, Samden D

2013-08-01

The epilepsy community increasingly recognizes the need for a modern classification system that can also be easily integrated with effective informatics tools. The 2010 reports by the United States President's Council of Advisors on Science and Technology (PCAST) identified informatics as a critical resource to improve quality of patient care, drive clinical research, and reduce the cost of health services. An effective informatics infrastructure for epilepsy, which is underpinned by a formal knowledge model or ontology, can leverage an ever increasing amount of multimodal data to improve (1) clinical decision support, (2) access to information for patients and their families, (3) easier data sharing, and (4) accelerate secondary use of clinical data. Modeling the recommendations of the International League Against Epilepsy (ILAE) classification system in the form of an epilepsy domain ontology is essential for consistent use of terminology in a variety of applications, including electronic health records systems and clinical applications. In this review, we discuss the data management issues in epilepsy and explore the benefits of an ontology-driven informatics infrastructure and its role in adoption of a "data-driven" paradigm in epilepsy research. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Epilepsy informatics and an ontology-driven infrastructure for large database research and patient care in epilepsy

PubMed Central

Sahoo, Satya S.; Zhang, Guo-Qiang; Lhatoo, Samden D.

2013-01-01

Summary The epilepsy community increasingly recognizes the need for a modern classification system that can also be easily integrated with effective informatics tools. The 2010 reports by the United States President's Council of Advisors on Science and Technology (PCAST) identified informatics as a critical resource to improve quality of patient care, drive clinical research, and reduce the cost of health services. An effective informatics infrastructure for epilepsy, which is underpinned by a formal knowledge model or ontology, can leverage an ever increasing amount of multimodal data to improve (1) clinical decision support, (2) access to information for patients and their families, (3) easier data sharing, and (4) accelerate secondary use of clinical data. Modeling the recommendations of the International League Against Epilepsy (ILAE) classification system in the form of an epilepsy domain ontology is essential for consistent use of terminology in a variety of applications, including electronic health records systems and clinical applications. In this review, we discuss the data management issues in epilepsy and explore the benefits of an ontology-driven informatics infrastructure and its role in adoption of a “data-driven” paradigm in epilepsy research. PMID:23647220

Technological Ecosystems in Health Informatics: A Brief Review Article.

PubMed

Wu, Zhongmei; Zhang, Xiuxiu; Chen, Ying; Zhang, Yan

2016-09-01

The existing models of information technology in health sciences have full scope of betterment and extension. The high demand pressures, public expectations, advanced platforms all collectively contribute towards hospital environment, which has to be kept in kind while designing of advanced technological ecosystem for information technology. Moreover, for the smooth conduct and operation of information system advanced management avenues are also essential in hospitals. It is the top priority of every hospital to deal with the essential needs of care for patients within the available resources of human and financial outputs. In these situations of high demand, the technological ecosystems in health informatics come in to play and prove its importance and role. The present review article would enlighten all these aspects of these ecosystems in hospital management and health care informatics. We searched the electronic database of MEDLINE, EMBASE, and PubMed for clinical controlled trials, pre-clinical studies reporting utilizaiono of ecosysyem advances in health information technology. The primary outcome of eligible studies included confirmation of importance and role of advances ecosystems in health informatics. It was observed that technological ecosystems are the backbone of health informatics. Advancements in technological ecosystems are essential for proper functioning of health information system in clinical setting.

A review of approaches to identifying patient phenotype cohorts using electronic health records

PubMed Central

Shivade, Chaitanya; Raghavan, Preethi; Fosler-Lussier, Eric; Embi, Peter J; Elhadad, Noemie; Johnson, Stephen B; Lai, Albert M

2014-01-01

Objective To summarize literature describing approaches aimed at automatically identifying patients with a common phenotype. Materials and methods We performed a review of studies describing systems or reporting techniques developed for identifying cohorts of patients with specific phenotypes. Every full text article published in (1) Journal of American Medical Informatics Association, (2) Journal of Biomedical Informatics, (3) Proceedings of the Annual American Medical Informatics Association Symposium, and (4) Proceedings of Clinical Research Informatics Conference within the past 3 years was assessed for inclusion in the review. Only articles using automated techniques were included. Results Ninety-seven articles met our inclusion criteria. Forty-six used natural language processing (NLP)-based techniques, 24 described rule-based systems, 41 used statistical analyses, data mining, or machine learning techniques, while 22 described hybrid systems. Nine articles described the architecture of large-scale systems developed for determining cohort eligibility of patients. Discussion We observe that there is a rise in the number of studies associated with cohort identification using electronic medical records. Statistical analyses or machine learning, followed by NLP techniques, are gaining popularity over the years in comparison with rule-based systems. Conclusions There are a variety of approaches for classifying patients into a particular phenotype. Different techniques and data sources are used, and good performance is reported on datasets at respective institutions. However, no system makes comprehensive use of electronic medical records addressing all of their known weaknesses. PMID:24201027

Improving usability and accessibility of cheminformatics tools for chemists through cyberinfrastructure and education.

PubMed

Guha, Rajarshi; Wiggins, Gary D; Wild, David J; Baik, Mu-Hyun; Pierce And, Marlon E; Fox, Geoffrey C

Some of the latest trends in cheminformatics, computation, and the world wide web are reviewed with predictions of how these are likely to impact the field of cheminformatics in the next five years. The vision and some of the work of the Chemical Informatics and Cyberinfrastructure Collaboratory at Indiana University are described, which we base around the core concepts of e-Science and cyberinfrastructure that have proven successful in other fields. Our chemical informatics cyberinfrastructure is realized by building a flexible, generic infrastructure for cheminformatics tools and databases, exporting "best of breed" methods as easily-accessible web APIs for cheminformaticians, scientists, and researchers in other disciplines, and hosting a unique chemical informatics education program aimed at scientists and cheminformatics practitioners in academia and industry.

The state and profile of open source software projects in health and medical informatics.

PubMed

Janamanchi, Balaji; Katsamakas, Evangelos; Raghupathi, Wullianallur; Gao, Wei

2009-07-01

Little has been published about the application profiles and development patterns of open source software (OSS) in health and medical informatics. This study explores these issues with an analysis of health and medical informatics related OSS projects on SourceForge, a large repository of open source projects. A search was conducted on the SourceForge website during the period from May 1 to 15, 2007, to identify health and medical informatics OSS projects. This search resulted in a sample of 174 projects. A Java-based parser was written to extract data for several of the key variables of each project. Several visually descriptive statistics were generated to analyze the profiles of the OSS projects. Many of the projects have sponsors, implying a growing interest in OSS among organizations. Sponsorship, we discovered, has a significant impact on project success metrics. Nearly two-thirds of the projects have a restrictive license type. Restrictive licensing may indicate tighter control over the development process. Our sample includes a wide range of projects that are at various stages of development (status). Projects targeted towards the advanced end user are primarily focused on bio-informatics, data formats, database and medical science applications. We conclude that there exists an active and thriving OSS development community that is focusing on health and medical informatics. A wide range of OSS applications are in development, from bio-informatics to hospital information systems. A profile of OSS in health and medical informatics emerges that is distinct and unique to the health care field. Future research can focus on OSS acceptance and diffusion and impact on cost, efficiency and quality of health care.

[The RUTA project (Registro UTIC Triveneto ANMCO). An e-network for the coronary care units for acute myocardial infarction].

PubMed

Di Chiara, Antonio; Zonzin, Pietro; Pavoni, Daisy; Fioretti, Paolo Maria

2003-06-01

In the era of evidence-based medicine, the monitoring of the adherence to the guidelines is fundamental, in order to verify the diagnostic and therapeutic processes. Informatic paperless databases allow a higher data quality, lower costs and timely analysis with overall advantages over the traditional surveys. The RUTA project (acronym of Triveneto Registry of ANMCO CCUs) was designed in 1999, aiming at creating an informatic network among the coronary care units of a large Italian region, for a permanent survey of patients admitted for acute myocardial infarction. Information ranges from the pre-hospital phase to discharge, including all relevant clinical and management variables. The database uses DBMS Personal Oracle and Power-Builder as user interface, on Windows platform. Anonymous data are sent to a central server.

An Optimized Informatics Pipeline for Mass Spectrometry-Based Peptidomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Chaochao; Monroe, Matthew E.; Xu, Zhe

2015-12-26

Comprehensive MS analysis of peptidome, the intracellular and intercellular products of protein degradation, has the potential to provide novel insights on endogenous proteolytic processing and their utility in disease diagnosis and prognosis. Along with the advances in MS instrumentation, a plethora of proteomics data analysis tools have been applied for direct use in peptidomics; however an evaluation of the currently available informatics pipelines for peptidomics data analysis has yet to be reported. In this study, we set off by evaluating the results of several popular MS/MS database search engines including MS-GF+, SEQUEST and MS-Align+ for peptidomics data analysis, followed bymore » identification and label-free quantification using the well-established accurate mass and time (AMT) tag and newly developed informed quantification (IQ) approaches, both based on direct LC-MS analysis. Our result demonstrated that MS-GF+ outperformed both SEQUEST and MS-Align+ in identifying peptidome peptides. Using a database established from the MS-GF+ peptide identifications, both the AMT tag and IQ approaches provided significantly deeper peptidome coverage and less missing value for each individual data set than the MS/MS methods, while achieving robust label-free quantification. Besides having an excellent correlation with the AMT tag quantification results, IQ also provided slightly higher peptidome coverage than AMT. Taken together, we propose an optimal informatics pipeline combining MS-GF+ for initial database searching with IQ (or AMT) for identification and label-free quantification for high-throughput, comprehensive and quantitative peptidomics analysis.« less

An overview of biomedical literature search on the World Wide Web in the third millennium.

PubMed

Kumar, Prince; Goel, Roshni; Jain, Chandni; Kumar, Ashish; Parashar, Abhishek; Gond, Ajay Ratan

2012-06-01

Complete access to the existing pool of biomedical literature and the ability to "hit" upon the exact information of the relevant specialty are becoming essential elements of academic and clinical expertise. With the rapid expansion of the literature database, it is almost impossible to keep up to date with every innovation. Using the Internet, however, most people can freely access this literature at any time, from almost anywhere. This paper highlights the use of the Internet in obtaining valuable biomedical research information, which is mostly available from journals, databases, textbooks and e-journals in the form of web pages, text materials, images, and so on. The authors present an overview of web-based resources for biomedical researchers, providing information about Internet search engines (e.g., Google), web-based bibliographic databases (e.g., PubMed, IndMed) and how to use them, and other online biomedical resources that can assist clinicians in reaching well-informed clinical decisions.

Life Sciences Data Archive (LSDA) in the Post-Shuttle Era

NASA Technical Reports Server (NTRS)

Fitts, Mary A.; Johnson-Throop, Kathy; Havelka, Jacque; Thomas, Diedre

2009-01-01

Now, more than ever before, NASA is realizing the value and importance of their intellectual assets. Principles of knowledge management, the systematic use and reuse of information/experience/expertise to achieve a specific goal, are being applied throughout the agency. LSDA is also applying these solutions, which rely on a combination of content and collaboration technologies, to enable research teams to create, capture, share, and harness knowledge to do the things they do well, even better. In the early days of spaceflight, space life sciences data were been collected and stored in numerous databases, formats, media-types and geographical locations. These data were largely unknown/unavailable to the research community. The Biomedical Informatics and Health Care Systems Branch of the Space Life Sciences Directorate at JSC and the Data Archive Project at ARC, with funding from the Human Research Program through the Exploration Medical Capability Element, are fulfilling these requirements through the systematic population of the Life Sciences Data Archive. This project constitutes a formal system for the acquisition, archival and distribution of data for HRP-related experiments and investigations. The general goal of the archive is to acquire, preserve, and distribute these data and be responsive to inquiries from the science communities.

[Scientometrics and bibliometrics of biomedical engineering periodicals and papers].

PubMed

Zhao, Ping; Xu, Ping; Li, Bingyan; Wang, Zhengrong

2003-09-01

This investigation was made to reveal the current status, research trend and research level of biomedical engineering in Chinese mainland by means of scientometrics and to assess the quality of the four domestic publications by bibliometrics. We identified all articles of four related publications by searching Chinese and foreign databases from 1997 to 2001. All articles collected or cited by these databases were searched and statistically analyzed for finding out the relevant distributions, including databases, years, authors, institutions, subject headings and subheadings. The source of sustentation funds and the related articles were analyzed too. The results showed that two journals were cited by two foreign databases and five Chinese databases simultaneously. The output of Journal of Biomedical Engineering was the highest. Its quantity of original papers cited by EI, CA and the totality of papers sponsored by funds were higher than those of the others, but the quantity and percentage per year of biomedical articles cited by EI were decreased in all. Inland core authors and institutions had come into being in the field of biomedical engineering. Their research topics were mainly concentrated on ten subject headings which included biocompatible materials, computer-assisted signal processing, electrocardiography, computer-assisted image processing, biomechanics, algorithms, electroencephalography, automatic data processing, mechanical stress, hemodynamics, mathematical computing, microcomputers, theoretical models, etc. The main subheadings were concentrated on instrumentation, physiopathology, diagnosis, therapy, ultrasonography, physiology, analysis, surgery, pathology, method, etc.

[Development and evaluation of the medical imaging distribution system with dynamic web application and clustering technology].

PubMed

Yokohama, Noriya; Tsuchimoto, Tadashi; Oishi, Masamichi; Itou, Katsuya

2007-01-20

It has been noted that the downtime of medical informatics systems is often long. Many systems encounter downtimes of hours or even days, which can have a critical effect on daily operations. Such systems remain especially weak in the areas of database and medical imaging data. The scheme design shows the three-layer architecture of the system: application, database, and storage layers. The application layer uses the DICOM protocol (Digital Imaging and Communication in Medicine) and HTTP (Hyper Text Transport Protocol) with AJAX (Asynchronous JavaScript+XML). The database is designed to decentralize in parallel using cluster technology. Consequently, restoration of the database can be done not only with ease but also with improved retrieval speed. In the storage layer, a network RAID (Redundant Array of Independent Disks) system, it is possible to construct exabyte-scale parallel file systems that exploit storage spread. Development and evaluation of the test-bed has been successful in medical information data backup and recovery in a network environment. This paper presents a schematic design of the new medical informatics system that can be accommodated from a recovery and the dynamic Web application for medical imaging distribution using AJAX.

The phytophthora genome initiative database: informatics and analysis for distributed pathogenomic research.

PubMed

Waugh, M; Hraber, P; Weller, J; Wu, Y; Chen, G; Inman, J; Kiphart, D; Sobral, B

2000-01-01

The Phytophthora Genome Initiative (PGI) is a distributed collaboration to study the genome and evolution of a particularly destructive group of plant pathogenic oomycete, with the goal of understanding the mechanisms of infection and resistance. NCGR provides informatics support for the collaboration as well as a centralized data repository. In the pilot phase of the project, several investigators prepared Phytophthora infestans and Phytophthora sojae EST and Phytophthora sojae BAC libraries and sent them to another laboratory for sequencing. Data from sequencing reactions were transferred to NCGR for analysis and curation. An analysis pipeline transforms raw data by performing simple analyses (i.e., vector removal and similarity searching) that are stored and can be retrieved by investigators using a web browser. Here we describe the database and access tools, provide an overview of the data therein and outline future plans. This resource has provided a unique opportunity for the distributed, collaborative study of a genus from which relatively little sequence data are available. Results may lead to insight into how better to control these pathogens. The homepage of PGI can be accessed at http:www.ncgr.org/pgi, with database access through the database access hyperlink.

Protein Bioinformatics Databases and Resources

PubMed Central

Chen, Chuming; Huang, Hongzhan; Wu, Cathy H.

2017-01-01

Many publicly available data repositories and resources have been developed to support protein related information management, data-driven hypothesis generation and biological knowledge discovery. To help researchers quickly find the appropriate protein related informatics resources, we present a comprehensive review (with categorization and description) of major protein bioinformatics databases in this chapter. We also discuss the challenges and opportunities for developing next-generation protein bioinformatics databases and resources to support data integration and data analytics in the Big Data era. PMID:28150231

[The biomedical periodicals of Hungarian editions--historical overview].

PubMed

Berhidi, Anna; Geges, József; Vasas, Lívia

2006-03-12

The majority of Hungarian scientific results are published in international periodicals in foreign languages. Yet the publications in Hungarian scientific periodicals also should not be ignored. This study analyses biomedical periodicals of Hungarian edition from different points of view. Based on different databases a list of titles consisting of 119 items resulted, which contains both the core and the peripheral journals of the biomedical field. These periodicals were analysed empirically, one by one: checking out the titles. 13 of the titles are ceased, among the rest 106 Hungarian scientific journals 10 are published in English language. From the remaining majority of Hungarian language and publishing only a few show up in international databases. Although quarter of the Hungarian biomedical journals meet the requirements, which means they could be represented in international databases, these periodicals are not indexed. 42 biomedical periodicals are available online. Although quarter of these journals come with restricted access. 2/3 of the Hungarian biomedical journals have detailed instructions to authors. These instructions inform the publishing doctors and researchers of the requirements of a biomedical periodical. The increasing number of Hungarian biomedical journals published is welcome news. But it would be important for quality publications which are cited a lot to appear in the Hungarian journals. The more publications are cited, the more journals and authors gain in prestige on home and international level.

Skills and knowledge of informatics, and training needs of hospital pharmacists in Thailand: A self-assessment survey.

PubMed

Chonsilapawit, Teeraporn; Rungpragayphan, Suang

2016-10-01

Because hospital pharmacists have to deal with large amounts of health information and advanced information technology in practice, they must possess adequate skills and knowledge of informatics to operate efficiently. However, most current pharmacy curricula in Thailand barely address the principles and skills concerned with informatics, and Thai pharmacists usually acquire computer literacy and informatics skills through personal-interest training and self-study. In this study, we aimed to assess the skills and knowledge of informatics and the training needs of hospital pharmacists in Thailand, in order to improve curricular and professional development. A self-assessment postal survey of 73 questions was developed and distributed to the pharmacy departments of 601 hospitals throughout the country. Practicing hospital pharmacists were requested to complete and return the survey voluntarily. Within the 3 months of the survey period, a total of 805 out of 2002 surveys were returned. On average, respondents rated themselves as competent or better in the skills of basic computer operation, the Internet, information management, and communication. Understandably, they rated themselves at novice level for information technology and database design knowledge/skills, and at advanced beginner level for project, risk, and change management skills. Respondents believed that skills and knowledge of informatics were highly necessary for their work, and definitely needed training. Thai hospital pharmacists were confident in using computers and the Internet. They realized and appreciated their lack of informatics knowledge and skills, and needed more training. Pharmacy curricula and training should be developed accordingly. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

caGrid 1.0: a Grid enterprise architecture for cancer research.

PubMed

Oster, Scott; Langella, Stephen; Hastings, Shannon; Ervin, David; Madduri, Ravi; Kurc, Tahsin; Siebenlist, Frank; Covitz, Peter; Shanbhag, Krishnakant; Foster, Ian; Saltz, Joel

2007-10-11

caGrid is the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG) program. The current release, caGrid version 1.0, is developed as the production Grid software infrastructure of caBIG. Based on feedback from adopters of the previous version (caGrid 0.5), it has been significantly enhanced with new features and improvements to existing components. This paper presents an overview of caGrid 1.0, its main components, and enhancements over caGrid 0.5.

Formalizing nursing knowledge: from theories and models to ontologies.

PubMed

Peace, Jane; Brennan, Patricia Flatley

2009-01-01

Knowledge representation in nursing is poised to address the depth of nursing knowledge about the specific phenomena of importance to nursing. Nursing theories and models may provide a starting point for making this knowledge explicit in representations. We combined knowledge building methods from nursing and ontology design methods from biomedical informatics to create a nursing representation of family health history. Our experience provides an example of how knowledge representations may be created to facilitate electronic support for nursing practice and knowledge development.

The Danish Microbiology Database (MiBa) 2010 to 2013.

PubMed

Voldstedlund, M; Haarh, M; Mølbak, K

2014-01-09

The Danish Microbiology Database (MiBa) is a national database that receives copies of reports from all Danish departments of clinical microbiology. The database was launched in order to provide healthcare personnel with nationwide access to microbiology reports and to enable real-time surveillance of communicable diseases and microorganisms. The establishment and management of MiBa has been a collaborative process among stakeholders, and the present paper summarises lessons learned from this nationwide endeavour which may be relevant to similar projects in the rapidly changing landscape of health informatics.

A comparison of traditional anti-inflammation and anti-infection medicinal plants with current evidence from biomedical research: Results from a regional study

PubMed Central

Vieira, A.

2010-01-01

Background: In relation to pharmacognosy, an objective of many ethnobotanical studies is to identify plant species to be further investigated, for example, tested in disease models related to the ethnomedicinal application. To further warrant such testing, research evidence for medicinal applications of these plants (or of their major phytochemical constituents and metabolic derivatives) is typically analyzed in biomedical databases. Methods: As a model of this process, the current report presents novel information regarding traditional anti-inflammation and anti-infection medicinal plant use. This information was obtained from an interview-based ethnobotanical study; and was compared with current biomedical evidence using the Medline® database. Results: Of the 8 anti-infection plant species identified in the ethnobotanical study, 7 have related activities reported in the database; and of the 6 anti-inflammation plants, 4 have related activities in the database. Conclusion: Based on novel and complimentary results from the ethnobotanical and biomedical database analyses, it is suggested that some of these plants warrant additional investigation of potential anti-inflammatory or anti-infection activities in related disease models, and also additional studies in other population groups. PMID:21589754

Unintended Consequences of Sensor, Signal, and Imaging Informatics: New Problems and New Solutions.

PubMed

Hughes, C; Voros, S; Moreau-Gaudry, A

2016-11-10

This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2016 of excellent research in the broad field of Sensor, Signal and Imaging Informatics published in the year 2015, with a focus on Unintended consequences: new problems and new solutions. We performed a systematic initial selection and a double blind peer review process to find the best papers in this domain published in 2015, from the PubMed and Web of Science databases. The set of MesH keywords used was provided by experts. The constant advances in medical technology allow ever more relevant diagnostic and therapeutic approaches to be designed. Nevertheless, there is a need to acquire expert knowledge of these innovations in order to identify precociously new associated problems for which new solutions need to be designed and developed.

Health informatics 3.0.

PubMed

Kalra, Dipak

2011-01-01

Web 3.0 promises us smart computer services that will interact with each other and leverage knowledge about us and our immediate context to deliver prioritised and relevant information to support decisions and actions. Healthcare must take advantage of such new knowledge-integrating services, in particular to support better co-operation between professionals of different disciplines working in different locations, and to enable well-informed co-operation between clinicians and patients. To grasp the potential of Web 3.0 we will need well-harmonised semantic resources that can richly connect virtual teams and link their strategies to real-time and tailored evidence. Facts, decision logic, care pathway steps, alerts, education need to be embedded within components that can interact with multiple EHR systems and services consistently. Using Health Informatics 3.0 a patient's current situation could be compared with the outcomes of very similar patients (from across millions) to deliver personalised care recommendations. The integration of EHRs with biomedical sciences ('omics) research results and predictive models such as the Virtual Physiological Human could help speed up the translation of new knowledge into clinical practice. The mission, and challenge, for Health Informatics 3.0 is to enable healthy citizens, patients and professionals to collaborate within a knowledge-empowered social network in which patient specific information and personalised real-time evidence are seamlessly interwoven.

The Stanford MediaServer Project: strategies for building a flexible digital media platform to support biomedical education and research.

PubMed Central

Durack, Jeremy C.; Chao, Chih-Chien; Stevenson, Derek; Andriole, Katherine P.; Dev, Parvati

2002-01-01

Medical media collections are growing at a pace that exceeds the value they currently provide as research and educational resources. To address this issue, the Stanford MediaServer was designed to promote innovative multimedia-based application development. The nucleus of the MediaServer platform is a digital media database strategically designed to meet the information needs of many biomedical disciplines. Key features include an intuitive web-based interface for collaboratively populating the media database, flexible creation of media collections for diverse and specialized purposes, and the ability to construct a variety of end-user applications from the same database to support biomedical education and research. PMID:12463820

The Stanford MediaServer Project: strategies for building a flexible digital media platform to support biomedical education and research.

PubMed

Durack, Jeremy C; Chao, Chih-Chien; Stevenson, Derek; Andriole, Katherine P; Dev, Parvati

2002-01-01

Medical media collections are growing at a pace that exceeds the value they currently provide as research and educational resources. To address this issue, the Stanford MediaServer was designed to promote innovative multimedia-based application development. The nucleus of the MediaServer platform is a digital media database strategically designed to meet the information needs of many biomedical disciplines. Key features include an intuitive web-based interface for collaboratively populating the media database, flexible creation of media collections for diverse and specialized purposes, and the ability to construct a variety of end-user applications from the same database to support biomedical education and research.

Health Informatics via Machine Learning for the Clinical Management of Patients.

PubMed

Clifton, D A; Niehaus, K E; Charlton, P; Colopy, G W

2015-08-13

To review how health informatics systems based on machine learning methods have impacted the clinical management of patients, by affecting clinical practice. We reviewed literature from 2010-2015 from databases such as Pubmed, IEEE xplore, and INSPEC, in which methods based on machine learning are likely to be reported. We bring together a broad body of literature, aiming to identify those leading examples of health informatics that have advanced the methodology of machine learning. While individual methods may have further examples that might be added, we have chosen some of the most representative, informative exemplars in each case. Our survey highlights that, while much research is taking place in this high-profile field, examples of those that affect the clinical management of patients are seldom found. We show that substantial progress is being made in terms of methodology, often by data scientists working in close collaboration with clinical groups. Health informatics systems based on machine learning are in their infancy and the translation of such systems into clinical management has yet to be performed at scale.

Resolving complex research data management issues in biomedical laboratories: Qualitative study of an industry-academia collaboration.

PubMed

Myneni, Sahiti; Patel, Vimla L; Bova, G Steven; Wang, Jian; Ackerman, Christopher F; Berlinicke, Cynthia A; Chen, Steve H; Lindvall, Mikael; Zack, Donald J

2016-04-01

This paper describes a distributed collaborative effort between industry and academia to systematize data management in an academic biomedical laboratory. Heterogeneous and voluminous nature of research data created in biomedical laboratories make information management difficult and research unproductive. One such collaborative effort was evaluated over a period of four years using data collection methods including ethnographic observations, semi-structured interviews, web-based surveys, progress reports, conference call summaries, and face-to-face group discussions. Data were analyzed using qualitative methods of data analysis to (1) characterize specific problems faced by biomedical researchers with traditional information management practices, (2) identify intervention areas to introduce a new research information management system called Labmatrix, and finally to (3) evaluate and delineate important general collaboration (intervention) characteristics that can optimize outcomes of an implementation process in biomedical laboratories. Results emphasize the importance of end user perseverance, human-centric interoperability evaluation, and demonstration of return on investment of effort and time of laboratory members and industry personnel for success of implementation process. In addition, there is an intrinsic learning component associated with the implementation process of an information management system. Technology transfer experience in a complex environment such as the biomedical laboratory can be eased with use of information systems that support human and cognitive interoperability. Such informatics features can also contribute to successful collaboration and hopefully to scientific productivity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

[Public scientific knowledge distribution in health information, communication and information technology indexed in MEDLINE and LILACS databases].

PubMed

Packer, Abel Laerte; Tardelli, Adalberto Otranto; Castro, Regina Célia Figueiredo

2007-01-01

This study explores the distribution of international, regional and national scientific output in health information and communication, indexed in the MEDLINE and LILACS databases, between 1996 and 2005. A selection of articles was based on the hierarchical structure of Information Science in MeSH vocabulary. Four specific domains were determined: health information, medical informatics, scientific communications on healthcare and healthcare communications. The variables analyzed were: most-covered subjects and journals, author affiliation and publication countries and languages, in both databases. The Information Science category is represented in nearly 5% of MEDLINE and LILACS articles. The four domains under analysis showed a relative annual increase in MEDLINE. The Medical Informatics domain showed the highest number of records in MEDLINE, representing about half of all indexed articles. The importance of Information Science as a whole is more visible in publications from developed countries and the findings indicate the predominance of the United States, with significant growth in scientific output from China and South Korea and, to a lesser extent, Brazil.

DataMed - an open source discovery index for finding biomedical datasets.

PubMed

Chen, Xiaoling; Gururaj, Anupama E; Ozyurt, Burak; Liu, Ruiling; Soysal, Ergin; Cohen, Trevor; Tiryaki, Firat; Li, Yueling; Zong, Nansu; Jiang, Min; Rogith, Deevakar; Salimi, Mandana; Kim, Hyeon-Eui; Rocca-Serra, Philippe; Gonzalez-Beltran, Alejandra; Farcas, Claudiu; Johnson, Todd; Margolis, Ron; Alter, George; Sansone, Susanna-Assunta; Fore, Ian M; Ohno-Machado, Lucila; Grethe, Jeffrey S; Xu, Hua

2018-01-13

Finding relevant datasets is important for promoting data reuse in the biomedical domain, but it is challenging given the volume and complexity of biomedical data. Here we describe the development of an open source biomedical data discovery system called DataMed, with the goal of promoting the building of additional data indexes in the biomedical domain. DataMed, which can efficiently index and search diverse types of biomedical datasets across repositories, is developed through the National Institutes of Health-funded biomedical and healthCAre Data Discovery Index Ecosystem (bioCADDIE) consortium. It consists of 2 main components: (1) a data ingestion pipeline that collects and transforms original metadata information to a unified metadata model, called DatA Tag Suite (DATS), and (2) a search engine that finds relevant datasets based on user-entered queries. In addition to describing its architecture and techniques, we evaluated individual components within DataMed, including the accuracy of the ingestion pipeline, the prevalence of the DATS model across repositories, and the overall performance of the dataset retrieval engine. Our manual review shows that the ingestion pipeline could achieve an accuracy of 90% and core elements of DATS had varied frequency across repositories. On a manually curated benchmark dataset, the DataMed search engine achieved an inferred average precision of 0.2033 and a precision at 10 (P@10, the number of relevant results in the top 10 search results) of 0.6022, by implementing advanced natural language processing and terminology services. Currently, we have made the DataMed system publically available as an open source package for the biomedical community. © The Author 2018. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A comparative analysis of moral principles and behavioral norms in eight ethical codes relevant to health sciences librarianship, medical informatics, and the health professions.

PubMed

Byrd, Gary D; Winkelstein, Peter

2014-10-01

Based on the authors' shared interest in the interprofessional challenges surrounding health information management, this study explores the degree to which librarians, informatics professionals, and core health professionals in medicine, nursing, and public health share common ethical behavior norms grounded in moral principles. Using the "Principlism" framework from a widely cited textbook of biomedical ethics, the authors analyze the statements in the ethical codes for associations of librarians (Medical Library Association [MLA], American Library Association, and Special Libraries Association), informatics professionals (American Medical Informatics Association [AMIA] and American Health Information Management Association), and core health professionals (American Medical Association, American Nurses Association, and American Public Health Association). This analysis focuses on whether and how the statements in these eight codes specify core moral norms (Autonomy, Beneficence, Non-Maleficence, and Justice), core behavioral norms (Veracity, Privacy, Confidentiality, and Fidelity), and other norms that are empirically derived from the code statements. These eight ethical codes share a large number of common behavioral norms based most frequently on the principle of Beneficence, then on Autonomy and Justice, but rarely on Non-Maleficence. The MLA and AMIA codes share the largest number of common behavioral norms, and these two associations also share many norms with the other six associations. The shared core of behavioral norms among these professions, all grounded in core moral principles, point to many opportunities for building effective interprofessional communication and collaboration regarding the development, management, and use of health information resources and technologies.

A comparative analysis of moral principles and behavioral norms in eight ethical codes relevant to health sciences librarianship, medical informatics, and the health professions

PubMed Central

Byrd, Gary D.; Winkelstein, Peter

2014-01-01

Objective: Based on the authors' shared interest in the interprofessional challenges surrounding health information management, this study explores the degree to which librarians, informatics professionals, and core health professionals in medicine, nursing, and public health share common ethical behavior norms grounded in moral principles. Methods: Using the “Principlism” framework from a widely cited textbook of biomedical ethics, the authors analyze the statements in the ethical codes for associations of librarians (Medical Library Association [MLA], American Library Association, and Special Libraries Association), informatics professionals (American Medical Informatics Association [AMIA] and American Health Information Management Association), and core health professionals (American Medical Association, American Nurses Association, and American Public Health Association). This analysis focuses on whether and how the statements in these eight codes specify core moral norms (Autonomy, Beneficence, Non-Maleficence, and Justice), core behavioral norms (Veracity, Privacy, Confidentiality, and Fidelity), and other norms that are empirically derived from the code statements. Results: These eight ethical codes share a large number of common behavioral norms based most frequently on the principle of Beneficence, then on Autonomy and Justice, but rarely on Non-Maleficence. The MLA and AMIA codes share the largest number of common behavioral norms, and these two associations also share many norms with the other six associations. Implications: The shared core of behavioral norms among these professions, all grounded in core moral principles, point to many opportunities for building effective interprofessional communication and collaboration regarding the development, management, and use of health information resources and technologies. PMID:25349543

Simplified Deployment of Health Informatics Applications by Providing Docker Images.

PubMed

Löbe, Matthias; Ganslandt, Thomas; Lotzmann, Lydia; Mate, Sebastian; Christoph, Jan; Baum, Benjamin; Sariyar, Murat; Wu, Jie; Stäubert, Sebastian

2016-01-01

Due to the specific needs of biomedical researchers, in-house development of software is widespread. A common problem is to maintain and enhance software after the funded project has ended. Even if many tools are made open source, only a couple of projects manage to attract a user basis large enough to ensure sustainability. Reasons for this include complex installation and configuration of biomedical software as well as an ambiguous terminology of the features provided; all of which make evaluation of software laborious. Docker is a para-virtualization technology based on Linux containers that eases deployment of applications and facilitates evaluation. We investigated a suite of software developments funded by a large umbrella organization for networked medical research within the last 10 years and created Docker containers for a number of applications to support utilization and dissemination.

Informatics applied to cytology

PubMed Central

Hornish, Maryanne; Goulart, Robert A.

2008-01-01

Automation and emerging information technologies are being adopted by cytology laboratories to augment Pap test screening and improve diagnostic accuracy. As a result, informatics, the application of computers and information systems to information management, has become essential for the successful operation of the cytopathology laboratory. This review describes how laboratory information management systems can be used to achieve an automated and seamless workflow process. The utilization of software, electronic databases and spreadsheets to perform necessary quality control measures are discussed, as well as a Lean production system and Six Sigma approach, to reduce errors in the cytopathology laboratory. PMID:19495402

The Visible Human Project of the National Library of Medicine: Remote access and distribution of a multi-gigabyte data set

NASA Technical Reports Server (NTRS)

Ackerman, Michael J.

1993-01-01

As part of the 1986 Long-Range Plan for the National Library of Medicine (NLM), the Planning Panel on Medical Education wrote that NLM should '...thoroughly and systematically investigate the technical requirements for and feasibility of instituting a biomedical images library.' The panel noted the increasing use of images in clinical practice and biomedical research. An image library would complement NLM's existing bibliographic and factual database services and would ideally be available through the same computer networks as are these current NLM services. Early in 1989, NLM's Board of Regents convened an ad hoc planning panel to explore possible roles for the NLM in the area of electronic image libraries. In its report to the Board of Regents, the NLM Planning Panel on Electronic Image Libraries recommended that 'NLM should undertake a first project building a digital image library of volumetric data representing a complete, normal adult male and female. This Visible Human Project will include digitized photographic images for cryosectioning, digital images derived from computerized tomography, and digital magnetic resonance images of cadavers.' The technologies needed to support digital high resolution image libraries, including rapid development; and that NLM encourage investigator-initiated research into methods for representing and linking spatial and textual information, structural informatics. The first part of the Visible Human Project is the acquisition of cross-sectional CT and MRI digital images and cross-sectional cryosectional photographic images of a representative male and female cadaver at an average of one millimeter intervals. The corresponding cross-sections in each of the three modalities are to be registerable with one another.

Using Informatics-, Bioinformatics- and Genomics-Based Approaches for the Molecular Surveillance and Detection of Biothreat Agents

NASA Astrophysics Data System (ADS)

Seto, Donald

The convergence and wealth of informatics, bioinformatics and genomics methods and associated resources allow a comprehensive and rapid approach for the surveillance and detection of bacterial and viral organisms. Coupled with the continuing race for the fastest, most cost-efficient and highest-quality DNA sequencing technology, that is, "next generation sequencing", the detection of biological threat agents by `cheaper and faster' means is possible. With the application of improved bioinformatic tools for the understanding of these genomes and for parsing unique pathogen genome signatures, along with `state-of-the-art' informatics which include faster computational methods, equipment and databases, it is feasible to apply new algorithms to biothreat agent detection. Two such methods are high-throughput DNA sequencing-based and resequencing microarray-based identification. These are illustrated and validated by two examples involving human adenoviruses, both from real-world test beds.

Extending XNAT Platform with an Incremental Semantic Framework

PubMed Central

Timón, Santiago; Rincón, Mariano; Martínez-Tomás, Rafael

2017-01-01

Informatics increases the yield from neuroscience due to improved data. Data sharing and accessibility enable joint efforts between different research groups, as well as replication studies, pivotal for progress in the field. Research data archiving solutions are evolving rapidly to address these necessities, however, distributed data integration is still difficult because of the need of explicit agreements for disparate data models. To address these problems, ontologies are widely used in biomedical research to obtain common vocabularies and logical descriptions, but its application may suffer from scalability issues, domain bias, and loss of low-level data access. With the aim of improving the application of semantic models in biobanking systems, an incremental semantic framework that takes advantage of the latest advances in biomedical ontologies and the XNAT platform is designed and implemented. We follow a layered architecture that allows the alignment of multi-domain biomedical ontologies to manage data at different levels of abstraction. To illustrate this approach, the development is integrated in the JPND (EU Joint Program for Neurodegenerative Disease) APGeM project, focused on finding early biomarkers for Alzheimer's and other dementia related diseases. PMID:28912709

Extending XNAT Platform with an Incremental Semantic Framework.

PubMed

Timón, Santiago; Rincón, Mariano; Martínez-Tomás, Rafael

2017-01-01

Informatics increases the yield from neuroscience due to improved data. Data sharing and accessibility enable joint efforts between different research groups, as well as replication studies, pivotal for progress in the field. Research data archiving solutions are evolving rapidly to address these necessities, however, distributed data integration is still difficult because of the need of explicit agreements for disparate data models. To address these problems, ontologies are widely used in biomedical research to obtain common vocabularies and logical descriptions, but its application may suffer from scalability issues, domain bias, and loss of low-level data access. With the aim of improving the application of semantic models in biobanking systems, an incremental semantic framework that takes advantage of the latest advances in biomedical ontologies and the XNAT platform is designed and implemented. We follow a layered architecture that allows the alignment of multi-domain biomedical ontologies to manage data at different levels of abstraction. To illustrate this approach, the development is integrated in the JPND (EU Joint Program for Neurodegenerative Disease) APGeM project, focused on finding early biomarkers for Alzheimer's and other dementia related diseases.

Bosnian and Herzegovinian medical scientists in PubMed database.

PubMed

Masic, Izet

2013-01-01

In this paper it is shortly presented PubMed as one of the most important on-line databases of the scientific biomedical literature. Also, the author has analyzed the most cited authors, professors of the medical faculties in Bosnia and Herzegovina, from the published papers in the biomedical journals abstracted and indexed in PubMed.

Where are Romanian biomedical journals now and what does the future hold for them? A scientometric analysis.

PubMed

Dumitrascu, Dan L

2018-01-01

There is a competition between scientific journals in order to achieve leadership in their scientific field. There are several Romanian biomedical journals which are published in English and a smaller number in Romanian. We need a periodical analysis of their visibility and ranking according to scientometric measures. We searched all biomedical journals indexed on international data bases: Web of Science, PubMed, Scopus, Embase, Google Scholar. We analyzed their evaluation factors. Several journals from Romania in the biomedical field are indexed in international databases. Their scientometric indexes are not high. The best journal was acquired by an international publisher and is no longer listed for Romania. There are several Romanian biomedical journals indexed in international databases that deserve periodical analysis. There is a need to improve their ranking.

Informatics in radiology: an information model of the DICOM standard.

PubMed

Kahn, Charles E; Langlotz, Curtis P; Channin, David S; Rubin, Daniel L

2011-01-01

The Digital Imaging and Communications in Medicine (DICOM) Standard is a key foundational technology for radiology. However, its complexity creates challenges for information system developers because the current DICOM specification requires human interpretation and is subject to nonstandard implementation. To address this problem, a formally sound and computationally accessible information model of the DICOM Standard was created. The DICOM Standard was modeled as an ontology, a machine-accessible and human-interpretable representation that may be viewed and manipulated by information-modeling tools. The DICOM Ontology includes a real-world model and a DICOM entity model. The real-world model describes patients, studies, images, and other features of medical imaging. The DICOM entity model describes connections between real-world entities and the classes that model the corresponding DICOM information entities. The DICOM Ontology was created to support the Cancer Biomedical Informatics Grid (caBIG) initiative, and it may be extended to encompass the entire DICOM Standard and serve as a foundation of medical imaging systems for research and patient care. RSNA, 2010

Convolving engineering and medical pedagogies for training of tomorrow's health care professionals.

PubMed

Lee, Raphael C

2013-03-01

Several fundamental benefits justify why biomedical engineering and medicine should form a more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers. Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the era of molecular biology well into today's era of molecular systems biology, which focuses on understanding the rules that govern the behavior of complex living systems. This has important medical implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in molecular systems biology to higher levels of biological organization (organ, system, and organismal levels) and then to develop new medical therapeutics based on simulation and medical informatics analysis. Higher education in biological and medical sciences must adapt to a new set of training objectives. This will involve a shifting away from reductionist problem solving toward more integrative, continuum, and predictive modeling approaches which traditionally have been more associated with engineering science. Future biomedical engineers and MDs must be able to predict clinical response to therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing rules of complex system behavior and skill sets in manipulating these systems to achieve a practical desired outcome are taught. Similarly, graduate biomedical engineering programs will include more practical exposure to clinical problem solving.

Translational Biomedical Informatics in the Cloud: Present and Future

PubMed Central

Chen, Jiajia; Qian, Fuliang; Yan, Wenying; Shen, Bairong

2013-01-01

Next generation sequencing and other high-throughput experimental techniques of recent decades have driven the exponential growth in publicly available molecular and clinical data. This information explosion has prepared the ground for the development of translational bioinformatics. The scale and dimensionality of data, however, pose obvious challenges in data mining, storage, and integration. In this paper we demonstrated the utility and promise of cloud computing for tackling the big data problems. We also outline our vision that cloud computing could be an enabling tool to facilitate translational bioinformatics research. PMID:23586054

caGrid 1.0: A Grid Enterprise Architecture for Cancer Research

PubMed Central

Oster, Scott; Langella, Stephen; Hastings, Shannon; Ervin, David; Madduri, Ravi; Kurc, Tahsin; Siebenlist, Frank; Covitz, Peter; Shanbhag, Krishnakant; Foster, Ian; Saltz, Joel

2007-01-01

caGrid is the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIGTM) program. The current release, caGrid version 1.0, is developed as the production Grid software infrastructure of caBIGTM. Based on feedback from adopters of the previous version (caGrid 0.5), it has been significantly enhanced with new features and improvements to existing components. This paper presents an overview of caGrid 1.0, its main components, and enhancements over caGrid 0.5. PMID:18693901

Advancing Systems Biology in the International Conference on Intelligent Biology and Medicine (ICIBM) 2015.

PubMed

Zhao, Zhongming; Liu, Yunlong; Huang, Yufei; Huang, Kun; Ruan, Jianhua

2016-08-26

The 2015 International Conference on Intelligent Biology and Medicine (ICIBM 2015) was held on November 13-15, 2015 in Indianapolis, Indiana, USA. ICIBM 2015 included eight scientific sessions, three tutorial sessions, one poster session, and four keynote presentations that covered the frontier research in broad areas related to bioinformatics, systems biology, big data science, biomedical informatics, pharmacogenomics, and intelligent computing. Here, we present a summary of the 10 research articles that were selected from ICIBM 2015 and included in the supplement to BMC Systems Biology.

Machine Learning Takes on Health Care: Leonard D'Avolio's Cyft Employs Big Data to Benefit Patients and Providers.

PubMed

Mertz, Leslie

2018-01-01

When Leonard D'Avolio (Figure 1) was working on his Ph.D. degree in biomedical informatics, he saw the power of machine learning in transforming multiple industries; health care, however, was not among them. "The reason that Amazon, Netflix, and Google have transformed their industries is because they have embedded learning throughout every aspect of what they do. If we could prove that is possible in health care too, I thought we would have the potential to have a huge impact," he says.

Cancer Imaging Phenomics Software Suite: Application to Brain and Breast Cancer | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The transition of oncologic imaging from its “industrial era” to it is “information era” demands analytical methods that 1) extract information from this data that is clinically and biologically relevant; 2) integrate imaging, clinical, and genomic data via rigorous statistical and computational methodologies in order to derive models valuable for understanding cancer mechanisms, diagnosis, prognostic assessment, response evaluation, and personalized treatment management; 3) are available to the biomedical community for easy use and application, with the aim of understanding, diagnosing, an

Applying a Participatory Design Approach to Define Objectives and Properties of a “Data Profiling” Tool for Electronic Health Data

PubMed Central

Estiri, Hossein; Lovins, Terri; Afzalan, Nader; Stephens, Kari A.

2016-01-01

We applied a participatory design approach to define the objectives, characteristics, and features of a “data profiling” tool for primary care Electronic Health Data (EHD). Through three participatory design workshops, we collected input from potential tool users who had experience working with EHD. We present 15 recommended features and characteristics for the data profiling tool. From these recommendations we derived three overarching objectives and five properties for the tool. A data profiling tool, in Biomedical Informatics, is a visual, clear, usable, interactive, and smart tool that is designed to inform clinical and biomedical researchers of data utility and let them explore the data, while conveniently orienting the users to the tool’s functionalities. We suggest that developing scalable data profiling tools will provide new capacities to disseminate knowledge about clinical data that will foster translational research and accelerate new discoveries. PMID:27570651

Should MD-PhD programs encourage graduate training in disciplines beyond conventional biomedical or clinical sciences?

PubMed

O'Mara, Ryan J; Hsu, Stephen I; Wilson, Daniel R

2015-02-01

The goal of MD-PhD training programs is to produce physician-scientists with unique capacities to lead the future biomedical research workforce. The current dearth of physician-scientists with expertise outside conventional biomedical or clinical sciences raises the question of whether MD-PhD training programs should allow or even encourage scholars to pursue doctoral studies in disciplines that are deemed nontraditional, yet are intrinsically germane to major influences on health. This question is especially relevant because the central value and ultimate goal of the academic medicine community is to help attain the highest level of health and health equity for all people. Advances in medical science and practice, along with improvements in health care access and delivery, are steps toward health equity, but alone they will not come close to eliminating health inequalities. Addressing the complex health issues in our communities and society as a whole requires a biomedical research workforce with knowledge, practice, and research skills well beyond conventional biomedical or clinical sciences. To make real progress in advancing health equity, educational pathways must prepare physician-scientists to treat both micro and macro determinants of health. The authors argue that MD-PhD programs should allow and encourage their scholars to cross boundaries into less traditional disciplines such as epidemiology, statistics, anthropology, sociology, ethics, public policy, management, economics, education, social work, informatics, communications, and marketing. To fulfill current and coming health care needs, nontraditional MD-PhD students should be welcomed and supported as valuable members of our biomedical research workforce.

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources.

PubMed

Huang, Yingxiang; Lee, Junghye; Wang, Shuang; Sun, Jimeng; Liu, Hongfang; Jiang, Xiaoqian

2018-05-16

Data sharing has been a big challenge in biomedical informatics because of privacy concerns. Contextual embedding models have demonstrated a very strong representative capability to describe medical concepts (and their context), and they have shown promise as an alternative way to support deep-learning applications without the need to disclose original data. However, contextual embedding models acquired from individual hospitals cannot be directly combined because their embedding spaces are different, and naive pooling renders combined embeddings useless. The aim of this study was to present a novel approach to address these issues and to promote sharing representation without sharing data. Without sacrificing privacy, we also aimed to build a global model from representations learned from local private data and synchronize information from multiple sources. We propose a methodology that harmonizes different local contextual embeddings into a global model. We used Word2Vec to generate contextual embeddings from each source and Procrustes to fuse different vector models into one common space by using a list of corresponding pairs as anchor points. We performed prediction analysis with harmonized embeddings. We used sequential medical events extracted from the Medical Information Mart for Intensive Care III database to evaluate the proposed methodology in predicting the next likely diagnosis of a new patient using either structured data or unstructured data. Under different experimental scenarios, we confirmed that the global model built from harmonized local models achieves a more accurate prediction than local models and global models built from naive pooling. Such aggregation of local models using our unique harmonization can serve as the proxy for a global model, combining information from a wide range of institutions and information sources. It allows information unique to a certain hospital to become available to other sites, increasing the fluidity of information flow in health care. ©Yingxiang Huang, Junghye Lee, Shuang Wang, Jimeng Sun, Hongfang Liu, Xiaoqian Jiang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 16.05.2018.

Biomedical science journals in the Arab world.

PubMed

Tadmouri, Ghazi O

2004-10-01

Medieval Arab scientists established the basis of medical practice and gave important attention to the publication of scientific results. At present, modern scientific publishing in the Arab world is in its developmental stage. Arab biomedical journals are less than 300, most of which are published in Egypt, Lebanon, and the Kingdom of Saudi Arabia. Yet, many of these journals do not have on-line access or are indexed in major bibliographic databases. The majority of indexed journals, however, do not have a stable presence in the popular PubMed database and their indexes are discontinued since 2001. The exposure of Arab biomedical journals in international indices undoubtedly plays an important role in improving the scientific quality of these journals. The successful examples discussed in this review encourage us to call for the formation of a consortium of Arab biomedical journal publishers to assist in redressing the balance of the region from biomedical data consumption to data production.

ExpoCastDB: A Publicly Accessible Database for Observational Exposure Data

EPA Science Inventory

The application of environmental informatics tools for human health risk assessment will require the development of advanced exposure information technology resources. Exposure data for chemicals is often not readily accessible. There is a pressing need for easily accessible, che...

Towards structured sharing of raw and derived neuroimaging data across existing resources

PubMed Central

Keator, D.B.; Helmer, K.; Steffener, J.; Turner, J.A.; Van Erp, T.G.M.; Gadde, S.; Ashish, N.; Burns, G.A.; Nichols, B.N.

2013-01-01

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery. PMID:23727024

Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues

PubMed Central

Han, Xu; Chiang, ChienWei; Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Li, Lang; Hennessy, Sean

2017-01-01

Background Drug-drug interactions with insulin secretagogues are associated with increased risk of serious hypoglycemia in patients with type 2 diabetes. We aimed to systematically screen for drugs that interact with the five most commonly used secretagogues―glipizide, glyburide, glimepiride, repaglinide, and nateglinide―to cause serious hypoglycemia. Methods We screened 400 drugs frequently co-prescribed with the secretagogues as candidate interacting precipitants. We first predicted the drug–drug interaction potential based on the pharmacokinetics of each secretagogue–precipitant pair. We then performed pharmacoepidemiologic screening for each secretagogue of interest, and for metformin as a negative control, using an administrative claims database and the self-controlled case series design. The overall rate ratios (RRs) and those for four predefined risk periods were estimated using Poisson regression. The RRs were adjusted for multiple estimation using semi-Bayes method, and then adjusted for metformin results to distinguish native effects of the precipitant from a drug–drug interaction. Results We predicted 34 pharmacokinetic drug–drug interactions with the secretagogues, nine moderate and 25 weak. There were 140 and 61 secretagogue–precipitant pairs associated with increased rates of serious hypoglycemia before and after the metformin adjustment, respectively. The results from pharmacokinetic prediction correlated poorly with those from pharmacoepidemiologic screening. Conclusions The self-controlled case series design has the potential to be widely applicable to screening for drug–drug interactions that lead to adverse outcomes identifiable in healthcare databases. Coupling pharmacokinetic prediction with pharmacoepidemiologic screening did not notably improve the ability to identify drug–drug interactions in this case. PMID:28169935

Opportunities at the Intersection of Bioinformatics and Health Informatics

PubMed Central

Miller, Perry L.

2000-01-01

This paper provides a “viewpoint discussion” based on a presentation made to the 2000 Symposium of the American College of Medical Informatics. It discusses potential opportunities for researchers in health informatics to become involved in the rapidly growing field of bioinformatics, using the activities of the Yale Center for Medical Informatics as a case study. One set of opportunities occurs where bioinformatics research itself intersects with the clinical world. Examples include the correlations between individual genetic variation with clinical risk factors, disease presentation, and differential response to treatment; and the implications of including genetic test results in the patient record, which raises clinical decision support issues as well as legal and ethical issues. A second set of opportunities occurs where bioinformatics research can benefit from the technologic expertise and approaches that informaticians have used extensively in the clinical arena. Examples include database organization and knowledge representation, data mining, and modeling and simulation. Microarray technology is discussed as a specific potential area for collaboration. Related questions concern how best to establish collaborations with bioscientists so that the interests and needs of both sets of researchers can be met in a synergistic fashion, and the most appropriate home for bioinformatics in an academic medical center. PMID:10984461

Implementation of the CDC translational informatics platform--from genetic variants to the national Swedish Rheumatology Quality Register.

PubMed

Abugessaisa, Imad; Gomez-Cabrero, David; Snir, Omri; Lindblad, Staffan; Klareskog, Lars; Malmström, Vivianne; Tegnér, Jesper

2013-04-02

Sequencing of the human genome and the subsequent analyses have produced immense volumes of data. The technological advances have opened new windows into genomics beyond the DNA sequence. In parallel, clinical practice generate large amounts of data. This represents an underused data source that has much greater potential in translational research than is currently realized. This research aims at implementing a translational medicine informatics platform to integrate clinical data (disease diagnosis, diseases activity and treatment) of Rheumatoid Arthritis (RA) patients from Karolinska University Hospital and their research database (biobanks, genotype variants and serology) at the Center for Molecular Medicine, Karolinska Institutet. Requirements engineering methods were utilized to identify user requirements. Unified Modeling Language and data modeling methods were used to model the universe of discourse and data sources. Oracle11g were used as the database management system, and the clinical development center (CDC) was used as the application interface. Patient data were anonymized, and we employed authorization and security methods to protect the system. We developed a user requirement matrix, which provided a framework for evaluating three translation informatics systems. The implementation of the CDC successfully integrated biological research database (15172 DNA, serum and synovial samples, 1436 cell samples and 65 SNPs per patient) and clinical database (5652 clinical visit) for the cohort of 379 patients presents three profiles. Basic functionalities provided by the translational medicine platform are research data management, development of bioinformatics workflow and analysis, sub-cohort selection, and re-use of clinical data in research settings. Finally, the system allowed researchers to extract subsets of attributes from cohorts according to specific biological, clinical, or statistical features. Research and clinical database integration is a real challenge and a road-block in translational research. Through this research we addressed the challenges and demonstrated the usefulness of CDC. We adhered to ethical regulations pertaining to patient data, and we determined that the existing software solutions cannot meet the translational research needs at hand. We used RA as a test case since we have ample data on active and longitudinal cohort.

Implementation of the CDC translational informatics platform - from genetic variants to the national Swedish Rheumatology Quality Register

PubMed Central

2013-01-01

Background Sequencing of the human genome and the subsequent analyses have produced immense volumes of data. The technological advances have opened new windows into genomics beyond the DNA sequence. In parallel, clinical practice generate large amounts of data. This represents an underused data source that has much greater potential in translational research than is currently realized. This research aims at implementing a translational medicine informatics platform to integrate clinical data (disease diagnosis, diseases activity and treatment) of Rheumatoid Arthritis (RA) patients from Karolinska University Hospital and their research database (biobanks, genotype variants and serology) at the Center for Molecular Medicine, Karolinska Institutet. Methods Requirements engineering methods were utilized to identify user requirements. Unified Modeling Language and data modeling methods were used to model the universe of discourse and data sources. Oracle11g were used as the database management system, and the clinical development center (CDC) was used as the application interface. Patient data were anonymized, and we employed authorization and security methods to protect the system. Results We developed a user requirement matrix, which provided a framework for evaluating three translation informatics systems. The implementation of the CDC successfully integrated biological research database (15172 DNA, serum and synovial samples, 1436 cell samples and 65 SNPs per patient) and clinical database (5652 clinical visit) for the cohort of 379 patients presents three profiles. Basic functionalities provided by the translational medicine platform are research data management, development of bioinformatics workflow and analysis, sub-cohort selection, and re-use of clinical data in research settings. Finally, the system allowed researchers to extract subsets of attributes from cohorts according to specific biological, clinical, or statistical features. Conclusions Research and clinical database integration is a real challenge and a road-block in translational research. Through this research we addressed the challenges and demonstrated the usefulness of CDC. We adhered to ethical regulations pertaining to patient data, and we determined that the existing software solutions cannot meet the translational research needs at hand. We used RA as a test case since we have ample data on active and longitudinal cohort. PMID:23548156

Gnome View: A tool for visual representation of human genome data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pelkey, J.E.; Thomas, G.S.; Thurman, D.A.

1993-02-01

GnomeView is a tool for exploring data generated by the Human Gemone Project. GnomeView provides both graphical and textural styles of data presentation: employs an intuitive window-based graphical query interface: and integrates its underlying genome databases in such a way that the user can navigate smoothly across databases and between different levels of data. This paper describes GnomeView and discusses how it addresses various genome informatics issues.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

The Importance of Biological Databases in Biological Discovery.

PubMed

Baxevanis, Andreas D; Bateman, Alex

2015-06-19

Biological databases play a central role in bioinformatics. They offer scientists the opportunity to access a wide variety of biologically relevant data, including the genomic sequences of an increasingly broad range of organisms. This unit provides a brief overview of major sequence databases and portals, such as GenBank, the UCSC Genome Browser, and Ensembl. Model organism databases, including WormBase, The Arabidopsis Information Resource (TAIR), and those made available through the Mouse Genome Informatics (MGI) resource, are also covered. Non-sequence-centric databases, such as Online Mendelian Inheritance in Man (OMIM), the Protein Data Bank (PDB), MetaCyc, and the Kyoto Encyclopedia of Genes and Genomes (KEGG), are also discussed. Copyright © 2015 John Wiley & Sons, Inc.

[Presence of the biomedical periodicals of Hungarian editions in international databases].

PubMed

Vasas, Lívia; Hercsel, Imréné

2006-01-15

Presence of the biomedical periodicals of Hungarian editions in international databases. The majority of Hungarian scientific results in medical and related sciences are published in scientific periodicals of foreign edition with high impact factor (IF) values, and they appear in international scientific literature in foreign languages. In this study the authors dealt with the presence and registered citation in international databases of those periodicals only, which had been published in Hungary and/or in cooperation with foreign publishing companies. The examination went back to year 1980 and covered a 25-year long period. 110 periodicals were selected for more detailed examination. The authors analyzed the situation of the current periodicals in the three most often visited databases (MEDLINE, EMBASE, Web of Science), and discovered, that the biomedical scientific periodicals of Hungarian interests were not represented with reasonable emphasis in the relevant international bibliographic databases. Because of the great number of data the scientific literature of medicine and related sciences could not be represented in its entirety, this publication, however, might give useful information for the inquirers, and call the attention of the competent people.

NCBI2RDF: enabling full RDF-based access to NCBI databases.

PubMed

Anguita, Alberto; García-Remesal, Miguel; de la Iglesia, Diana; Maojo, Victor

2013-01-01

RDF has become the standard technology for enabling interoperability among heterogeneous biomedical databases. The NCBI provides access to a large set of life sciences databases through a common interface called Entrez. However, the latter does not provide RDF-based access to such databases, and, therefore, they cannot be integrated with other RDF-compliant databases and accessed via SPARQL query interfaces. This paper presents the NCBI2RDF system, aimed at providing RDF-based access to the complete NCBI data repository. This API creates a virtual endpoint for servicing SPARQL queries over different NCBI repositories and presenting to users the query results in SPARQL results format, thus enabling this data to be integrated and/or stored with other RDF-compliant repositories. SPARQL queries are dynamically resolved, decomposed, and forwarded to the NCBI-provided E-utilities programmatic interface to access the NCBI data. Furthermore, we show how our approach increases the expressiveness of the native NCBI querying system, allowing several databases to be accessed simultaneously. This feature significantly boosts productivity when working with complex queries and saves time and effort to biomedical researchers. Our approach has been validated with a large number of SPARQL queries, thus proving its reliability and enhanced capabilities in biomedical environments.

A multilingual gold-standard corpus for biomedical concept recognition: the Mantra GSC.

PubMed

Kors, Jan A; Clematide, Simon; Akhondi, Saber A; van Mulligen, Erik M; Rebholz-Schuhmann, Dietrich

2015-09-01

To create a multilingual gold-standard corpus for biomedical concept recognition. We selected text units from different parallel corpora (Medline abstract titles, drug labels, biomedical patent claims) in English, French, German, Spanish, and Dutch. Three annotators per language independently annotated the biomedical concepts, based on a subset of the Unified Medical Language System and covering a wide range of semantic groups. To reduce the annotation workload, automatically generated preannotations were provided. Individual annotations were automatically harmonized and then adjudicated, and cross-language consistency checks were carried out to arrive at the final annotations. The number of final annotations was 5530. Inter-annotator agreement scores indicate good agreement (median F-score 0.79), and are similar to those between individual annotators and the gold standard. The automatically generated harmonized annotation set for each language performed equally well as the best annotator for that language. The use of automatic preannotations, harmonized annotations, and parallel corpora helped to keep the manual annotation efforts manageable. The inter-annotator agreement scores provide a reference standard for gauging the performance of automatic annotation techniques. To our knowledge, this is the first gold-standard corpus for biomedical concept recognition in languages other than English. Other distinguishing features are the wide variety of semantic groups that are being covered, and the diversity of text genres that were annotated. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Physical Science Informatics: Providing Open Science Access to Microheater Array Boiling Experiment Data

NASA Technical Reports Server (NTRS)

McQuillen, John; Green, Robert D.; Henrie, Ben; Miller, Teresa; Chiaramonte, Fran

2014-01-01

The Physical Science Informatics (PSI) system is the next step in this an effort to make NASA sponsored flight data available to the scientific and engineering community, along with the general public. The experimental data, from six overall disciplines, Combustion Science, Fluid Physics, Complex Fluids, Fundamental Physics, and Materials Science, will present some unique challenges. Besides data in textual or numerical format, large portions of both the raw and analyzed data for many of these experiments are digital images and video, requiring large data storage requirements. In addition, the accessible data will include experiment design and engineering data (including applicable drawings), any analytical or numerical models, publications, reports, and patents, and any commercial products developed as a result of the research. This objective of paper includes the following: Present the preliminary layout (Figure 2) of MABE data within the PSI database. Obtain feedback on the layout. Present the procedure to obtain access to this database.

Linking Supermarket Sales Data To Nutritional Information: An Informatics Feasibility Study

PubMed Central

Brinkerhoff, Kristina M.; Brewster, Philip J.; Clark, Edward B.; Jordan, Kristine C.; Cummins, Mollie R.; Hurdle, John F.

2011-01-01

Grocery sales are a data source of potential value to dietary assessment programs in public health informatics. However, the lack of a computable method for mapping between nutrient and food item information represents a major obstacle. We studied the feasibility of linking point-of-sale data to USDA-SR nutrient database information in a sustainable way. We analyzed 2,009,533 de-identified sales items purchased by 32,785 customers over a two-week period. We developed a method using the item category hierarchy in the supermarket’s database to link purchased items to records from the USDA-SR. We describe our methodology and its rationale and limitations. Approximately 70% of all items were mapped and linked to the SR; approximately 90% of all items could be mapped with an equivalent expenditure of additional effort. 100% of all items were mapped to USDA standard food groups. We conclude that mapping grocery sales data to nutritional information is feasible. PMID:22195115

Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness.

PubMed

Herasevich, Vitaly; Pickering, Brian W; Dong, Yue; Peters, Steve G; Gajic, Ognjen

2010-03-01

To develop and validate an informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Using open-schema data feeds imported from electronic medical records (EMRs), we developed a near-real-time relational database (Multidisciplinary Epidemiology and Translational Research in Intensive Care Data Mart). Imported data domains included physiologic monitoring, medication orders, laboratory and radiologic investigations, and physician and nursing notes. Open database connectivity supported the use of Boolean combinations of data that allowed authorized users to develop syndrome surveillance, decision support, and reporting (data "sniffers") routines. Random samples of database entries in each category were validated against corresponding independent manual reviews. The Multidisciplinary Epidemiology and Translational Research in Intensive Care Data Mart accommodates, on average, 15,000 admissions to the intensive care unit (ICU) per year and 200,000 vital records per day. Agreement between database entries and manual EMR audits was high for sex, mortality, and use of mechanical ventilation (kappa, 1.0 for all) and for age and laboratory and monitored data (Bland-Altman mean difference +/- SD, 1(0) for all). Agreement was lower for interpreted or calculated variables, such as specific syndrome diagnoses (kappa, 0.5 for acute lung injury), duration of ICU stay (mean difference +/- SD, 0.43+/-0.2), or duration of mechanical ventilation (mean difference +/- SD, 0.2+/-0.9). Extraction of essential ICU data from a hospital EMR into an open, integrative database facilitates process control, reporting, syndrome surveillance, decision support, and outcome research in the ICU.

MSBIS: A Multi-Step Biomedical Informatics Screening Approach for Identifying Medications that Mitigate the Risks of Metoclopramide-Induced Tardive Dyskinesia.

PubMed

Xu, Dong; Ham, Alexandrea G; Tivis, Rickey D; Caylor, Matthew L; Tao, Aoxiang; Flynn, Steve T; Economen, Peter J; Dang, Hung K; Johnson, Royal W; Culbertson, Vaughn L

2017-12-01

In 2009 the U.S. Food and Drug Administration (FDA) placed a black box warning on metoclopramide (MCP) due to the increased risks and prevalence of tardive dyskinesia (TD). In this study, we developed a multi-step biomedical informatics screening (MSBIS) approach leveraging publicly available bioactivity and drug safety data to identify concomitant drugs that mitigate the risks of MCP-induced TD. MSBIS includes (1) TargetSearch (http://dxulab.org/software) bioinformatics scoring for drug anticholinergic activity using CHEMBL bioactivity data; (2) unadjusted odds ratio (UOR) scoring for indications of TD-mitigating effects using the FDA Adverse Event Reporting System (FAERS); (3) adjusted odds ratio (AOR) re-scoring by removing the effect of cofounding factors (age, gender, reporting year); (4) logistic regression (LR) coefficient scoring for confirming the best TD-mitigating drug candidates. Drugs with increasing TD protective potential and statistical significance were obtained at each screening step. Fentanyl is identified as the most promising drug against MCP-induced TD (coefficient: -2.68; p-value<0.01). The discovery is supported by clinical reports that patients fully recovered from MCP-induced TD after fentanyl-induced general anesthesia. Loperamide is identified as a potent mitigating drug against a broader range of drug-induced movement disorders through pharmacokinetic modifications. Using drug-induced TD as an example, we demonstrated that MSBIS is an efficient in silico tool for unknown drug-drug interaction detection, drug repurposing, and combination therapy design. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Applications of information and communications technologies to public health: A scoping review using the MeSH term: "public health informatics".

PubMed

Bhattarai, Arjun Kumar; Zarrin, Aein; Lee, Joon

2017-01-01

To investigate the public health domains, key informatics concepts, and information and communications technologies (ICTs) applied in articles that are tagged with the MeSH term "public health informatics" and primarily focus on applying ICTs to public health. The MeSH term "public health informatics" was searched on MEDLINE-PubMed. The results of the search were then screened in two steps in order to only include articles about applying ICTs to public health problems. First, articles were screened based on their titles and abstracts. Second, a full-text review was conducted to ensure the relevance of the included articles. All articles were charted based on public health domain, information technology, article type, and informatics concept. 515 articles were included. Communicable disease monitoring (N=235), public health policy and research (N=201), and public health awareness (N=85) constituted the majority of the articles. Inconsistent results were found regarding the validity of syndromic surveillance and the effectiveness of PHI integration within the healthcare systems. PHI articles with an ICT focus cover a wide range of themes. Collectively, the included articles emphasized the need for further research in interoperability, data quality, appropriate data sources, accessible health information, and communication. The limitations of the study include:1) only one database was searched; 2) by using MeSH tags as a selection criterion, PHI articles without the "public health informatics" MeSH term were excluded. Due to the multi-disciplinary nature of PHI, MeSH identifiers were not assigned consistently. Current MeSH-tagged articles indicate that a comprehensive approach is required to integrate PHI into the healthcare system.

ACToR Chemical Structure processing using Open Source ChemInformatics Libraries (FutureToxII)

EPA Science Inventory

ACToR (Aggregated Computational Toxicology Resource) is a centralized database repository developed by the National Center for Computational Toxicology (NCCT) at the U.S. Environmental Protection Agency (EPA). Free and open source tools were used to compile toxicity data from ove...

Clinical nursing informatics. Developing tools for knowledge workers.

PubMed

Ozbolt, J G; Graves, J R

1993-06-01

Current research in clinical nursing informatics is proceeding along three important dimensions: (1) identifying and defining nursing's language and structuring its data; (2) understanding clinical judgment and how computer-based systems can facilitate and not replace it; and (3) discovering how well-designed systems can transform nursing practice. A number of efforts are underway to find and use language that accurately represents nursing and that can be incorporated into computer-based information systems. These efforts add to understanding nursing problems, interventions, and outcomes, and provide the elements for databases from which nursing's costs and effectiveness can be studied. Research on clinical judgment focuses on how nurses (perhaps with different levels of expertise) assess patient needs, set goals, and plan and deliver care, as well as how computer-based systems can be developed to aid these cognitive processes. Finally, investigators are studying not only how computers can help nurses with the mechanics and logistics of processing information but also and more importantly how access to informatics tools changes nursing care.

caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability.

PubMed

Komatsoulis, George A; Warzel, Denise B; Hartel, Francis W; Shanbhag, Krishnakant; Chilukuri, Ram; Fragoso, Gilberto; Coronado, Sherri de; Reeves, Dianne M; Hadfield, Jillaine B; Ludet, Christophe; Covitz, Peter A

2008-02-01

One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service-Oriented Architecture (SSOA) for cancer research by the National Cancer Institute's cancer Biomedical Informatics Grid (caBIG).

caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability

PubMed Central

Komatsoulis, George A.; Warzel, Denise B.; Hartel, Frank W.; Shanbhag, Krishnakant; Chilukuri, Ram; Fragoso, Gilberto; de Coronado, Sherri; Reeves, Dianne M.; Hadfield, Jillaine B.; Ludet, Christophe; Covitz, Peter A.

2008-01-01

One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service Oriented Architecture (SSOA) for cancer research by the National Cancer Institute’s cancer Biomedical Informatics Grid (caBIG™). PMID:17512259

The educational needs of health information managers in an electronic environment: what information technology and health informatics skills and knowledge are required?

PubMed

Robertson, Merryn; Callen, Joanne

The profile of health information managers (HIMs) employed within one metropolitan area health service in New South Wales (NSW) was identified, together with which information technology and health informatics knowledge and skills they possess, and which ones they require in their workplace. The subjects worked in a variety of roles: 26% were employed in the area's Information Systems Division developing and implementing point-of-care clinical systems. Health information managers perceived they needed further continuing and formal education in point-of-care clinical systems, decision support systems, the electronic health record, privacy and security, health data collections, and database applications.

Finding relevant biomedical datasets: the UC San Diego solution for the bioCADDIE Retrieval Challenge

PubMed Central

Wei, Wei; Ji, Zhanglong; He, Yupeng; Zhang, Kai; Ha, Yuanchi; Li, Qi; Ohno-Machado, Lucila

2018-01-01

Abstract The number and diversity of biomedical datasets grew rapidly in the last decade. A large number of datasets are stored in various repositories, with different formats. Existing dataset retrieval systems lack the capability of cross-repository search. As a result, users spend time searching datasets in known repositories, and they typically do not find new repositories. The biomedical and healthcare data discovery index ecosystem (bioCADDIE) team organized a challenge to solicit new indexing and searching strategies for retrieving biomedical datasets across repositories. We describe the work of one team that built a retrieval pipeline and examined its performance. The pipeline used online resources to supplement dataset metadata, automatically generated queries from users’ free-text questions, produced high-quality retrieval results and achieved the highest inferred Normalized Discounted Cumulative Gain among competitors. The results showed that it is a promising solution for cross-database, cross-domain and cross-repository biomedical dataset retrieval. Database URL: https://github.com/w2wei/dataset_retrieval_pipeline PMID:29688374

User needs analysis and usability assessment of DataMed - a biomedical data discovery index.

PubMed

Dixit, Ram; Rogith, Deevakar; Narayana, Vidya; Salimi, Mandana; Gururaj, Anupama; Ohno-Machado, Lucila; Xu, Hua; Johnson, Todd R

2017-11-30

To present user needs and usability evaluations of DataMed, a Data Discovery Index (DDI) that allows searching for biomedical data from multiple sources. We conducted 2 phases of user studies. Phase 1 was a user needs analysis conducted before the development of DataMed, consisting of interviews with researchers. Phase 2 involved iterative usability evaluations of DataMed prototypes. We analyzed data qualitatively to document researchers' information and user interface needs. Biomedical researchers' information needs in data discovery are complex, multidimensional, and shaped by their context, domain knowledge, and technical experience. User needs analyses validate the need for a DDI, while usability evaluations of DataMed show that even though aggregating metadata into a common search engine and applying traditional information retrieval tools are promising first steps, there remain challenges for DataMed due to incomplete metadata and the complexity of data discovery. Biomedical data poses distinct problems for search when compared to websites or publications. Making data available is not enough to facilitate biomedical data discovery: new retrieval techniques and user interfaces are necessary for dataset exploration. Consistent, complete, and high-quality metadata are vital to enable this process. While available data and researchers' information needs are complex and heterogeneous, a successful DDI must meet those needs and fit into the processes of biomedical researchers. Research directions include formalizing researchers' information needs, standardizing overviews of data to facilitate relevance judgments, implementing user interfaces for concept-based searching, and developing evaluation methods for open-ended discovery systems such as DDIs. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

About the Cancer Biomarkers Research Group | Division of Cancer Prevention

Cancer.gov

The Cancer Biomarkers Research Group promotes research to identify, develop, and validate biological markers for early cancer detection and cancer risk assessment. Activities include development and validation of promising cancer biomarkers, collaborative databases and informatics systems, and new technologies or the refinement of existing technologies. NCI DCP News Note

From Databases to Modelling of Functional Pathways

PubMed Central

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell. PMID:18629070

From databases to modelling of functional pathways.

PubMed

Nasi, Sergio

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell.

Next Generation Clustered Heat Maps | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Next-Generation (Clustered) Heat Maps are interactive heat maps that enable the user to zoom and pan across the heatmap, alter its color scheme, generate production quality PDFs, and link out from rows, columns, and individual heatmap entries to related statistics, databases and other information.

NCBI2RDF: Enabling Full RDF-Based Access to NCBI Databases

PubMed Central

Anguita, Alberto; García-Remesal, Miguel; de la Iglesia, Diana; Maojo, Victor

2013-01-01

RDF has become the standard technology for enabling interoperability among heterogeneous biomedical databases. The NCBI provides access to a large set of life sciences databases through a common interface called Entrez. However, the latter does not provide RDF-based access to such databases, and, therefore, they cannot be integrated with other RDF-compliant databases and accessed via SPARQL query interfaces. This paper presents the NCBI2RDF system, aimed at providing RDF-based access to the complete NCBI data repository. This API creates a virtual endpoint for servicing SPARQL queries over different NCBI repositories and presenting to users the query results in SPARQL results format, thus enabling this data to be integrated and/or stored with other RDF-compliant repositories. SPARQL queries are dynamically resolved, decomposed, and forwarded to the NCBI-provided E-utilities programmatic interface to access the NCBI data. Furthermore, we show how our approach increases the expressiveness of the native NCBI querying system, allowing several databases to be accessed simultaneously. This feature significantly boosts productivity when working with complex queries and saves time and effort to biomedical researchers. Our approach has been validated with a large number of SPARQL queries, thus proving its reliability and enhanced capabilities in biomedical environments. PMID:23984425

Biomedical journals and databases in Russia and Russian language in the former Soviet Union and beyond

PubMed Central

Vlassov, Vasiliy V; Danishevskiy, Kirill D

2008-01-01

In the 20th century, Russian biomedical science experienced a decline from the blossom of the early years to a drastic state. Through the first decades of the USSR, it was transformed to suit the ideological requirements of a totalitarian state and biased directives of communist leaders. Later, depressing economic conditions and isolation from the international research community further impeded its development. Contemporary Russia has inherited a system of medical education quite different from the west as well as counterproductive regulations for the allocation of research funding. The methodology of medical and epidemiological research in Russia is largely outdated. Epidemiology continues to focus on infectious disease and results of the best studies tend to be published in international periodicals. MEDLINE continues to be the best database to search for Russian biomedical publications, despite only a small proportion being indexed. The database of the Moscow Central Medical Library is the largest national database of medical periodicals, but does not provide abstracts and full subject heading codes, and it does not cover even the entire collection of the Library. New databases and catalogs (e.g. Panteleimon) that have appeared recently are incomplete and do not enable effective searching. PMID:18826569

Biomedical journals and databases in Russia and Russian language in the former Soviet Union and beyond.

PubMed

Vlassov, Vasiliy V; Danishevskiy, Kirill D

2008-09-30

In the 20th century, Russian biomedical science experienced a decline from the blossom of the early years to a drastic state. Through the first decades of the USSR, it was transformed to suit the ideological requirements of a totalitarian state and biased directives of communist leaders. Later, depressing economic conditions and isolation from the international research community further impeded its development. Contemporary Russia has inherited a system of medical education quite different from the west as well as counterproductive regulations for the allocation of research funding. The methodology of medical and epidemiological research in Russia is largely outdated. Epidemiology continues to focus on infectious disease and results of the best studies tend to be published in international periodicals. MEDLINE continues to be the best database to search for Russian biomedical publications, despite only a small proportion being indexed. The database of the Moscow Central Medical Library is the largest national database of medical periodicals, but does not provide abstracts and full subject heading codes, and it does not cover even the entire collection of the Library. New databases and catalogs (e.g. Panteleimon) that have appeared recently are incomplete and do not enable effective searching.

Automated detection of discourse segment and experimental types from the text of cancer pathway results sections.

PubMed

Burns, Gully A P C; Dasigi, Pradeep; de Waard, Anita; Hovy, Eduard H

2016-01-01

Automated machine-reading biocuration systems typically use sentence-by-sentence information extraction to construct meaning representations for use by curators. This does not directly reflect the typical discourse structure used by scientists to construct an argument from the experimental data available within a article, and is therefore less likely to correspond to representations typically used in biomedical informatics systems (let alone to the mental models that scientists have). In this study, we develop Natural Language Processing methods to locate, extract, and classify the individual passages of text from articles' Results sections that refer to experimental data. In our domain of interest (molecular biology studies of cancer signal transduction pathways), individual articles may contain as many as 30 small-scale individual experiments describing a variety of findings, upon which authors base their overall research conclusions. Our system automatically classifies discourse segments in these texts into seven categories (fact, hypothesis, problem, goal, method, result, implication) with an F-score of 0.68. These segments describe the essential building blocks of scientific discourse to (i) provide context for each experiment, (ii) report experimental details and (iii) explain the data's meaning in context. We evaluate our system on text passages from articles that were curated in molecular biology databases (the Pathway Logic Datum repository, the Molecular Interaction MINT and INTACT databases) linking individual experiments in articles to the type of assay used (coprecipitation, phosphorylation, translocation etc.). We use supervised machine learning techniques on text passages containing unambiguous references to experiments to obtain baseline F1 scores of 0.59 for MINT, 0.71 for INTACT and 0.63 for Pathway Logic. Although preliminary, these results support the notion that targeting information extraction methods to experimental results could provide accurate, automated methods for biocuration. We also suggest the need for finer-grained curation of experimental methods used when constructing molecular biology databases. © The Author(s) 2016. Published by Oxford University Press.

E-Learning as New Method of Medical Education

PubMed Central

Masic, Izet

2008-01-01

CONFLICT OF INTEREST: NONE DECLARED Distance learning refers to use of technologies based on health care delivered on distance and covers areas such as electronic health, tele-health (e-health), telematics, telemedicine, tele-education, etc. For the need of e-health, telemedicine, tele-education and distance learning there are various technologies and communication systems from standard telephone lines to the system of transmission digitalized signals with modem, optical fiber, satellite links, wireless technologies, etc. Tele-education represents health education on distance, using Information Communication Technologies (ICT), as well as continuous education of a health system beneficiaries and use of electronic libraries, data bases or electronic data with data bases of knowledge. Distance learning (E-learning) as a part of tele-education has gained popularity in the past decade; however, its use is highly variable among medical schools and appears to be more common in basic medical science courses than in clinical education. Distance learning does not preclude traditional learning processes; frequently it is used in conjunction with in-person classroom or professional training procedures and practices. Tele-education has mostly been used in biomedical education as a blended learning method, which combines tele-education technology with traditional instructor-led training, where, for example, a lecture or demonstration is supplemented by an online tutorial. Distance learning is used for self-education, tests, services and for examinations in medicine i.e. in terms of self-education and individual examination services. The possibility of working in the exercise mode with image files and questions is an attractive way of self education. Automated tracking and reporting of learners’ activities lessen faculty administrative burden. Moreover, e-learning can be designed to include outcomes assessment to determine whether learning has occurred. This review article evaluates the current status and level of tele-education development in Bosnia and Herzegovina outlining its components, faculty development needs for implementation and the possibility of its integration as official learning standard in biomedical curricula in Bosnia and Herzegovina. Tele-education refers to the use of information and communication technologies (ICT) to enhance knowledge and performance. Tele-education in biomedical education is widely accepted in the medical education community where it is mostly integrated into biomedical curricula forming part of a blended learning strategy. There are many biomedical digital repositories of e-learning materials worldwide, some peer reviewed, where instructors or developers can submit materials for widespread use. First pilot project with the aim to introduce tele-education in biomedical curricula in Bosnia and Herzegovina was initiated by Department for Medical Informatics at Medical Faculty in Sarajevo in 2002 and has been developing since. Faculty member’s skills in creating tele-education differ from those needed for traditional teaching and faculty rewards must recognize this difference and reward the effort. Tele-education and use of computers will have an impact of future medical practice in a life long learning. Bologna process, which started last years in European countries, provide us to promote and introduce modern educational methods of education at biomedical faculties in Bosnia and Herzegovina. Cathedra of Medical informatics and Cathedra of Family medicine at Medical Faculty of University of Sarajevo started to use Web based education as common way of teaching of medical students. Satisfaction with this method of education within the students is good, but not yet suitable for most of medical disciplines at biomedical faculties in Bosnia and Herzegovina. PMID:24109154

E-learning as new method of medical education.

PubMed

Masic, Izet

2008-01-01

NONE DECLARED Distance learning refers to use of technologies based on health care delivered on distance and covers areas such as electronic health, tele-health (e-health), telematics, telemedicine, tele-education, etc. For the need of e-health, telemedicine, tele-education and distance learning there are various technologies and communication systems from standard telephone lines to the system of transmission digitalized signals with modem, optical fiber, satellite links, wireless technologies, etc. Tele-education represents health education on distance, using Information Communication Technologies (ICT), as well as continuous education of a health system beneficiaries and use of electronic libraries, data bases or electronic data with data bases of knowledge. Distance learning (E-learning) as a part of tele-education has gained popularity in the past decade; however, its use is highly variable among medical schools and appears to be more common in basic medical science courses than in clinical education. Distance learning does not preclude traditional learning processes; frequently it is used in conjunction with in-person classroom or professional training procedures and practices. Tele-education has mostly been used in biomedical education as a blended learning method, which combines tele-education technology with traditional instructor-led training, where, for example, a lecture or demonstration is supplemented by an online tutorial. Distance learning is used for self-education, tests, services and for examinations in medicine i.e. in terms of self-education and individual examination services. The possibility of working in the exercise mode with image files and questions is an attractive way of self education. Automated tracking and reporting of learners' activities lessen faculty administrative burden. Moreover, e-learning can be designed to include outcomes assessment to determine whether learning has occurred. This review article evaluates the current status and level of tele-education development in Bosnia and Herzegovina outlining its components, faculty development needs for implementation and the possibility of its integration as official learning standard in biomedical curricula in Bosnia and Herzegovina. Tele-education refers to the use of information and communication technologies (ICT) to enhance knowledge and performance. Tele-education in biomedical education is widely accepted in the medical education community where it is mostly integrated into biomedical curricula forming part of a blended learning strategy. There are many biomedical digital repositories of e-learning materials worldwide, some peer reviewed, where instructors or developers can submit materials for widespread use. First pilot project with the aim to introduce tele-education in biomedical curricula in Bosnia and Herzegovina was initiated by Department for Medical Informatics at Medical Faculty in Sarajevo in 2002 and has been developing since. Faculty member's skills in creating tele-education differ from those needed for traditional teaching and faculty rewards must recognize this difference and reward the effort. Tele-education and use of computers will have an impact of future medical practice in a life long learning. Bologna process, which started last years in European countries, provide us to promote and introduce modern educational methods of education at biomedical faculties in Bosnia and Herzegovina. Cathedra of Medical informatics and Cathedra of Family medicine at Medical Faculty of University of Sarajevo started to use Web based education as common way of teaching of medical students. Satisfaction with this method of education within the students is good, but not yet suitable for most of medical disciplines at biomedical faculties in Bosnia and Herzegovina.

caGrid 1.0: An Enterprise Grid Infrastructure for Biomedical Research

PubMed Central

Oster, Scott; Langella, Stephen; Hastings, Shannon; Ervin, David; Madduri, Ravi; Phillips, Joshua; Kurc, Tahsin; Siebenlist, Frank; Covitz, Peter; Shanbhag, Krishnakant; Foster, Ian; Saltz, Joel

2008-01-01

Objective To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. Design An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG™) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including 1) discovery, 2) integrated and large-scale data analysis, and 3) coordinated study. Measurements The caGrid is built as a Grid software infrastructure and leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. Results The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid. Conclusions While caGrid 1.0 is designed to address use cases in cancer research, the requirements associated with discovery, analysis and integration of large scale data, and coordinated studies are common in other biomedical fields. In this respect, caGrid 1.0 is the realization of a framework that can benefit the entire biomedical community. PMID:18096909

caGrid 1.0: an enterprise Grid infrastructure for biomedical research.

PubMed

Oster, Scott; Langella, Stephen; Hastings, Shannon; Ervin, David; Madduri, Ravi; Phillips, Joshua; Kurc, Tahsin; Siebenlist, Frank; Covitz, Peter; Shanbhag, Krishnakant; Foster, Ian; Saltz, Joel

2008-01-01

To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including 1) discovery, 2) integrated and large-scale data analysis, and 3) coordinated study. The caGrid is built as a Grid software infrastructure and leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid. While caGrid 1.0 is designed to address use cases in cancer research, the requirements associated with discovery, analysis and integration of large scale data, and coordinated studies are common in other biomedical fields. In this respect, caGrid 1.0 is the realization of a framework that can benefit the entire biomedical community.

Clinical Research Informatics: Challenges, Opportunities and Definition for an Emerging Domain

PubMed Central

Embi, Peter J.; Payne, Philip R.O.

2009-01-01

Objectives Clinical Research Informatics, an emerging sub-domain of Biomedical Informatics, is currently not well defined. A formal description of CRI including major challenges and opportunities is needed to direct progress in the field. Design Given the early stage of CRI knowledge and activity, we engaged in a series of qualitative studies with key stakeholders and opinion leaders to determine the range of challenges and opportunities facing CRI. These phases employed complimentary methods to triangulate upon our findings. Measurements Study phases included: 1) a group interview with key stakeholders, 2) an email follow-up survey with a larger group of self-identified CRI professionals, and 3) validation of our results via electronic peer-debriefing and member-checking with a group of CRI-related opinion leaders. Data were collected, transcribed, and organized for formal, independent content analyses by experienced qualitative investigators, followed by an iterative process to identify emergent categorizations and thematic descriptions of the data. Results We identified a range of challenges and opportunities facing the CRI domain. These included 13 distinct themes spanning academic, practical, and organizational aspects of CRI. These findings also informed the development of a formal definition of CRI and supported further representations that illustrate areas of emphasis critical to advancing the domain. Conclusions CRI has emerged as a distinct discipline that faces multiple challenges and opportunities. The findings presented summarize those challenges and opportunities and provide a framework that should help inform next steps to advance this important new discipline. PMID:19261934

GRATEFUL MED

EPA Science Inventory

Since the early 1970s, the National Library of Medicine (NLM) has made searching the biomedical literature faster and easier by providing online information on NLMs family of databases -- (currently 40 online databases). MEDLINE?, NLMs premier database, has over 8.5 million citat...

An Online Database Producer's Memoirs and Memories of an Online Pioneer and The Database Industry: Looking into the Future.

ERIC Educational Resources Information Center

Kollegger, James G.; And Others

1988-01-01

In the first of three articles, the producer of Energyline, Energynet, and Tele/Scope recalls the development of the databases and database business strategies. The second describes the development of biomedical online databases, and the third discusses future developments, including full text databases, database producers as online host, and…

Identification of biomedical journals in Spain and Latin America.

PubMed

Bonfill, Xavier; Osorio, Dimelza; Posso, Margarita; Solà, Ivan; Rada, Gabriel; Torres, Ania; García Dieguez, Marcelo; Piña-Pozas, Maricela; Díaz-García, Luisa; Tristán, Mario; Gandarilla, Omar; Rincón-Valenzuela, David A; Martí, Arturo; Hidalgo, Ricardo; Simancas-Racines, Daniel; López, Luis; Correa, Ricardo; Rojas-De-Arias, Antonieta; Loza, César; Gianneo, Óscar; Pardo, Hector

2015-12-01

Journals in languages other than English that publish original clinical research are often not well covered in the main biomedical databases and therefore often not included in systematic reviews. This study aimed to identify Spanish language biomedical journals from Spain and Latin America and to describe their main features. Journals were identified in electronic databases, publishers' catalogues and local registries. Eligibility was determined by assessing data from these sources or the journals' websites, when available. A total of 2457 journals were initially identified; 1498 met inclusion criteria. Spain (27.3%), Mexico (16.0%), Argentina (15.1%) and Chile (11.9%) had the highest number of journals. Most (85.8%) are currently active; 87.8% have an ISSN. The median and mean length of publication were 22 and 29 years, respectively. A total of 66.0% were indexed in at least one database; 3.0% had an impact factor in 2012. A total of 845 journals had websites (56.4%), of which 700 (82.8%) were searchable and 681 (80.6%) free of charge. Most of the identified journals have no impact factor or are not indexed in any of the major databases. The list of identified biomedical journals can be a useful resource when conducting hand searching activities and identifying clinical trials that otherwise would not be retrieved. © 2015 Health Libraries Group.

AST commercial human space flight biomedical data collection

DOT National Transportation Integrated Search

2007-02-01

Recommendations are made for specific biomedical data, equipment, and a database that will increase the knowledge and understanding of how short duration, suborbital space flight missions with brief exposure to microgravity affects the human body. Th...

[Over- or underestimated? Bibliographic survey of the biomedical periodicals published in Hungary].

PubMed

Berhidi, Anna; Horváth, Katalin; Horváth, Gabriella; Vasas, Lívia

2013-06-30

This publication - based on an article published in 2006 - emphasises the qualities of the current biomedical periodicals of Hungarian editions. The aim of this study was to analyse how Hungarian journals meet the requirements of the scientific aspect and international visibility. Authors evaluated 93 Hungarian biomedical periodicals by 4 viewpoints of the two criteria mentioned above. 35% of the analysed journals complete the attributes of scientific aspect, 5% the international visibility, 6% fulfill all examined criteria, and 25% are indexed in international databases. 6 biomedical Hungarian periodicals covered by each of the three main bibliographic databases (Medline, Scopus, Web of Science) have the best qualities. Authors recommend to improve viewpoints of the scientific aspect and international visibility. The basis of qualitative adequacy are the accurate authors' guidelines, title, abstract, keywords of the articles in English, and the ability to publish on time.

A Diagram Editor for Efficient Biomedical Knowledge Capture and Integration

PubMed Central

Yu, Bohua; Jakupovic, Elvis; Wilson, Justin; Dai, Manhong; Xuan, Weijian; Mirel, Barbara; Athey, Brian; Watson, Stanley; Meng, Fan

2008-01-01

Understanding the molecular mechanisms underlying complex disorders requires the integration of data and knowledge from different sources including free text literature and various biomedical databases. To facilitate this process, we created the Biomedical Concept Diagram Editor (BCDE) to help researchers distill knowledge from data and literature and aid the process of hypothesis development. A key feature of BCDE is the ability to capture information with a simple drag-and-drop. This is a vast improvement over manual methods of knowledge and data recording and greatly increases the efficiency of the biomedical researcher. BCDE also provides a unique concept matching function to enforce consistent terminology, which enables conceptual relationships deposited by different researchers in the BCDE database to be mined and integrated for intelligible and useful results. We hope BCDE will promote the sharing and integration of knowledge from different researchers for effective hypothesis development. PMID:21347131

DeTEXT: A Database for Evaluating Text Extraction from Biomedical Literature Figures

PubMed Central

Yin, Xu-Cheng; Yang, Chun; Pei, Wei-Yi; Man, Haixia; Zhang, Jun; Learned-Miller, Erik; Yu, Hong

2015-01-01

Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. Since text is a rich source of information in figures, automatically extracting such text may assist in the task of mining figure information. A high-quality ground truth standard can greatly facilitate the development of an automated system. This article describes DeTEXT: A database for evaluating text extraction from biomedical literature figures. It is the first publicly available, human-annotated, high quality, and large-scale figure-text dataset with 288 full-text articles, 500 biomedical figures, and 9308 text regions. This article describes how figures were selected from open-access full-text biomedical articles and how annotation guidelines and annotation tools were developed. We also discuss the inter-annotator agreement and the reliability of the annotations. We summarize the statistics of the DeTEXT data and make available evaluation protocols for DeTEXT. Finally we lay out challenges we observed in the automated detection and recognition of figure text and discuss research directions in this area. DeTEXT is publicly available for downloading at http://prir.ustb.edu.cn/DeTEXT/. PMID:25951377

Automated identification of molecular effects of drugs (AIMED)

PubMed Central

Fathiamini, Safa; Johnson, Amber M; Zeng, Jia; Araya, Alejandro; Holla, Vijaykumar; Bailey, Ann M; Litzenburger, Beate C; Sanchez, Nora S; Khotskaya, Yekaterina; Xu, Hua; Meric-Bernstam, Funda; Bernstam, Elmer V

2016-01-01

Introduction Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant information is rapidly emerging in the literature and elsewhere, there is a need for informatics technologies to support targeted therapies. To this end, we have developed a system for Automated Identification of Molecular Effects of Drugs, to help biomedical scientists curate this literature to facilitate decision support. Objectives To create an automated system to identify assertions in the literature concerning drugs targeting genes with therapeutic implications and characterize the challenges inherent in automating this process in rapidly evolving domains. Methods We used subject-predicate-object triples (semantic predications) and co-occurrence relations generated by applying the SemRep Natural Language Processing system to MEDLINE abstracts and ClinicalTrials.gov descriptions. We applied customized semantic queries to find drugs targeting genes of interest. The results were manually reviewed by a team of experts. Results Compared to a manually curated set of relationships, recall, precision, and F2 were 0.39, 0.21, and 0.33, respectively, which represents a 3- to 4-fold improvement over a publically available set of predications (SemMedDB) alone. Upon review of ostensibly false positive results, 26% were considered relevant additions to the reference set, and an additional 61% were considered to be relevant for review. Adding co-occurrence data improved results for drugs in early development, but not their better-established counterparts. Conclusions Precision medicine poses unique challenges for biomedical informatics systems that help domain experts find answers to their research questions. Further research is required to improve the performance of such systems, particularly for drugs in development. PMID:27107438

How to Search, Write, Prepare and Publish the Scientific Papers in the Biomedical Journals

PubMed Central

Masic, Izet

2011-01-01

This article describes the methodology of preparation, writing and publishing scientific papers in biomedical journals. given is a concise overview of the concept and structure of the System of biomedical scientific and technical information and the way of biomedical literature retreival from worldwide biomedical databases. Described are the scientific and professional medical journals that are currently published in Bosnia and Herzegovina. Also, given is the comparative review on the number and structure of papers published in indexed journals in Bosnia and Herzegovina, which are listed in the Medline database. Analyzed are three B&H journals indexed in MEDLINE database: Medical Archives (Medicinski Arhiv), Bosnian Journal of Basic Medical Sciences and Medical Gazette (Medicinki Glasnik) in 2010. The largest number of original papers was published in the Medical Archives. There is a statistically significant difference in the number of papers published by local authors in relation to international journals in favor of the Medical Archives. True, the Journal Bosnian Journal of Basic Medical Sciences does not categorize the articles and we could not make comparisons. Journal Medical Archives and Bosnian Journal of Basic Medical Sciences by percentage published the largest number of articles by authors from Sarajevo and Tuzla, the two oldest and largest university medical centers in Bosnia and Herzegovina. The author believes that it is necessary to make qualitative changes in the reception and reviewing of papers for publication in biomedical journals published in Bosnia and Herzegovina which should be the responsibility of the separate scientific authority/ committee composed of experts in the field of medicine at the state level. PMID:23572850

What Is eHealth (4): A Scoping Exercise to Map the Field

PubMed Central

Sloan, David; Gregor, Peter; Sullivan, Frank; Detmer, Don; Kahan, James P; Oortwijn, Wija; MacGillivray, Steve

2005-01-01

Background Lack of consensus on the meaning of eHealth has led to uncertainty among academics, policymakers, providers and consumers. This project was commissioned in light of the rising profile of eHealth on the international policy agenda and the emerging UK National Programme for Information Technology (now called Connecting for Health) and related developments in the UK National Health Service. Objectives To map the emergence and scope of eHealth as a topic and to identify its place within the wider health informatics field, as part of a larger review of research and expert analysis pertaining to current evidence, best practice and future trends. Methods Multiple databases of scientific abstracts were explored in a nonsystematic fashion to assess the presence of eHealth or conceptually related terms within their taxonomies, to identify journals in which articles explicitly referring to eHealth are contained and the topics covered, and to identify published definitions of the concept. The databases were Medline (PubMed), the Cumulative Index of Nursing and Allied Health Literature (CINAHL), the Science Citation Index (SCI), the Social Science Citation Index (SSCI), the Cochrane Database (including Dare, Central, NHS Economic Evaluation Database [NHS EED], Health Technology Assessment [HTA] database, NHS EED bibliographic) and ISTP (now known as ISI proceedings).We used the search query, “Ehealth OR e-health OR e*health”. The timeframe searched was 1997-2003, although some analyses contain data emerging subsequent to this period. This was supplemented by iterative searches of Web-based sources, such as commercial and policy reports, research commissioning programmes and electronic news pages. Definitions extracted from both searches were thematically analyzed and compared in order to assess conceptual heterogeneity. Results The term eHealth only came into use in the year 2000, but has since become widely prevalent. The scope of the topic was not immediately discernable from that of the wider health informatics field, for which over 320000 publications are listed in Medline alone, and it is not explicitly represented within the existing Medical Subject Headings (MeSH) taxonomy. Applying eHealth as narrative search term to multiple databases yielded 387 relevant articles, distributed across 154 different journals, most commonly related to information technology and telemedicine, but extending to such areas as law. Most eHealth articles are represented on Medline. Definitions of eHealth vary with respect to the functions, stakeholders, contexts and theoretical issues targeted. Most encompass a broad range of medical informatics applications either specified (eg, decision support, consumer health information) or presented in more general terms (eg, to manage, arrange or deliver health care). However the majority emphasize the communicative functions of eHealth and specify the use of networked digital technologies, primarily the Internet, thus differentiating eHealth from the field of medical informatics. While some definitions explicitly target health professionals or patients, most encompass applications for all stakeholder groups. The nature of the scientific and broader literature pertaining to eHealth closely reflects these conceptualizations. Conclusions We surmise that the field – as it stands today – may be characterized by the global definitions suggested by Eysenbach and Eng. PMID:15829481

A survey of quality assurance practices in biomedical open source software projects.

PubMed

Koru, Günes; El Emam, Khaled; Neisa, Angelica; Umarji, Medha

2007-05-07

Open source (OS) software is continuously gaining recognition and use in the biomedical domain, for example, in health informatics and bioinformatics. Given the mission critical nature of applications in this domain and their potential impact on patient safety, it is important to understand to what degree and how effectively biomedical OS developers perform standard quality assurance (QA) activities such as peer reviews and testing. This would allow the users of biomedical OS software to better understand the quality risks, if any, and the developers to identify process improvement opportunities to produce higher quality software. A survey of developers working on biomedical OS projects was conducted to examine the QA activities that are performed. We took a descriptive approach to summarize the implementation of QA activities and then examined some of the factors that may be related to the implementation of such practices. Our descriptive results show that 63% (95% CI, 54-72) of projects did not include peer reviews in their development process, while 82% (95% CI, 75-89) did include testing. Approximately 74% (95% CI, 67-81) of developers did not have a background in computing, 80% (95% CI, 74-87) were paid for their contributions to the project, and 52% (95% CI, 43-60) had PhDs. A multivariate logistic regression model to predict the implementation of peer reviews was not significant (likelihood ratio test = 16.86, 9 df, P = .051) and neither was a model to predict the implementation of testing (likelihood ratio test = 3.34, 9 df, P = .95). Less attention is paid to peer review than testing. However, the former is a complementary, and necessary, QA practice rather than an alternative. Therefore, one can argue that there are quality risks, at least at this point in time, in transitioning biomedical OS software into any critical settings that may have operational, financial, or safety implications. Developers of biomedical OS applications should invest more effort in implementing systemic peer review practices throughout the development and maintenance processes.

Virtual biomedical universities and e-learning.

PubMed

Beux, P Le; Fieschi, M

2007-01-01

In this special issue on virtual biomedical universities and e-learning we will make a survey on the principal existing teaching applications of ICT used in medical Schools around the world. In the following we identify five types of research and experiments in this field of medical e-learning and virtual medical universities. The topics of this special issue goes from educational computer program to create and simulate virtual patients with a wide variety of medical conditions in different clinical settings and over different time frames to using distance learning in developed and developing countries program training medical informatics of clinicians. We also present the necessity of good indexing and research tools for training resources together with workflows to manage the multiple source content of virtual campus or universities and the virtual digital video resources. A special attention is given to training new generations of clinicians in ICT tools and methods to be used in clinical settings as well as in medical schools.

Access to Core Facilities and Other Research Resources Provided by the Clinical and Translational Science Awards

PubMed Central

2012-01-01

Abstract  Principal investigators who received Clinical and Translational Science Awards created academic homes for biomedical research. They developed program‐supported websites to offer coordinated access to a range of core facilities and other research resources. Visitors to the 60 websites will find at least 170 generic services, which this review has categorized in the following seven areas: (1) core facilities, (2) biomedical informatics, (3) funding, (4) regulatory knowledge and support, (5) biostatistics, epidemiology, research design, and ethics, (6) participant and clinical interaction resources, and (7) community engagement. In addition, many websites facilitate access to resources with search engines, navigators, studios, project development teams, collaboration tools, communication systems, and teaching tools. Each of these websites may be accessed from a single site, http://www.CTSAcentral.org. The ability to access the research resources from 60 of the nation's academic health centers presents a novel opportunity for investigators engaged in clinical and translational research. Clin Trans Sci 2012; Volume #: 1–5 PMID:22376262

A methodology for extending domain coverage in SemRep.

PubMed

Rosemblat, Graciela; Shin, Dongwook; Kilicoglu, Halil; Sneiderman, Charles; Rindflesch, Thomas C

2013-12-01

We describe a domain-independent methodology to extend SemRep coverage beyond the biomedical domain. SemRep, a natural language processing application originally designed for biomedical texts, uses the knowledge sources provided by the Unified Medical Language System (UMLS©). Ontological and terminological extensions to the system are needed in order to support other areas of knowledge. We extended SemRep's application by developing a semantic representation of a previously unsupported domain. This was achieved by adapting well-known ontology engineering phases and integrating them with the UMLS knowledge sources on which SemRep crucially depends. While the process to extend SemRep coverage has been successfully applied in earlier projects, this paper presents in detail the step-wise approach we followed and the mechanisms implemented. A case study in the field of medical informatics illustrates how the ontology engineering phases have been adapted for optimal integration with the UMLS. We provide qualitative and quantitative results, which indicate the validity and usefulness of our methodology. Published by Elsevier Inc.

Using Galaxy to Perform Large-Scale Interactive Data Analyses

PubMed Central

Hillman-Jackson, Jennifer; Clements, Dave; Blankenberg, Daniel; Taylor, James; Nekrutenko, Anton

2014-01-01

Innovations in biomedical research technologies continue to provide experimental biologists with novel and increasingly large genomic and high-throughput data resources to be analyzed. As creating and obtaining data has become easier, the key decision faced by many researchers is a practical one: where and how should an analysis be performed? Datasets are large and analysis tool set-up and use is riddled with complexities outside of the scope of core research activities. The authors believe that Galaxy provides a powerful solution that simplifies data acquisition and analysis in an intuitive Web application, granting all researchers access to key informatics tools previously only available to computational specialists working in Unix-based environments. We will demonstrate through a series of biomedically relevant protocols how Galaxy specifically brings together (1) data retrieval from public and private sources, for example, UCSC's Eukaryote and Microbial Genome Browsers, (2) custom tools (wrapped Unix functions, format standardization/conversions, interval operations), and 3rd-party analysis tools. PMID:22700312

Access to core facilities and other research resources provided by the Clinical and Translational Science Awards.

PubMed

Rosenblum, Daniel

2012-02-01

Principal investigators who received Clinical and Translational Science Awards created academic homes for biomedical research. They developed program-supported websites to offer coordinated access to a range of core facilities and other research resources. Visitors to the 60 websites will find at least 170 generic services, which this review has categorized in the following seven areas: (1) core facilities, (2) biomedical informatics, (3) funding, (4) regulatory knowledge and support, (5) biostatistics, epidemiology, research design, and ethics, (6) participant and clinical interaction resources, and (7) community engagement. In addition, many websites facilitate access to resources with search engines, navigators, studios, project development teams, collaboration tools, communication systems, and teaching tools. Each of these websites may be accessed from a single site, http://www.CTSAcentral.org. The ability to access the research resources from 60 of the nation's academic health centers presents a novel opportunity for investigators engaged in clinical and translational research. © 2012 Wiley Periodicals, Inc.

An integrated high resolution mass spectrometric and informatics approach for the rapid identification of phenolics in plant extract

USDA-ARS?s Scientific Manuscript database

An integrated approach based on high resolution MS analysis (orbitrap), database (db) searching and MS/MS fragmentation prediction for the rapid identification of plant phenols is reported. The approach was firstly validated by using a mixture of phenolic standards (phenolic acids, flavones, flavono...

Informatics approach using metabolic reactivity classifiers to link in vitro to in vivo data in application to the ToxCast Phase I dataset

EPA Science Inventory

Strategic combinations and tiered application of alternative testing methods to replace or minimize the use of animal models is attracting much attention. With the advancement of high throughput screening (HTS) assays and legacy databases providing in vivo testing results, suffic...

PubChem applications in drug discovery: a bibliometric analysis

PubMed Central

Cheng, Tiejun; Pan, Yongmei; Hao, Ming; Wang, Yanli; Bryant, Stephen H.

2014-01-01

A bibliometric analysis of PubChem applications is presented by reviewing 1132 research articles. The massive volume of chemical structure and bioactivity data in PubChem and its online services has been used globally in various fields including chemical biology, medicinal chemistry and informatics research. PubChem supports drug discovery in many aspects such as lead identification and optimization, compound–target profiling, polypharmacology studies and unknown chemical identity elucidation. PubChem has also become a valuable resource for developing secondary databases, informatics tools and web services. The growing PubChem resource with its public availability offers support and great opportunities for the interrogation of pharmacological mechanisms and the genetic basis of diseases, which are vital for drug innovation and repurposing. PMID:25168772

Evaluation of a joint Bioinformatics and Medical Informatics international course in Peru

PubMed Central

Curioso, Walter H; Hansen, Jacquelyn R; Centurion-Lara, Arturo; Garcia, Patricia J; Wolf, Fredric M; Fuller, Sherrilynne; Holmes, King K; Kimball, Ann Marie

2008-01-01

Background New technologies that emerge at the interface of computational and biomedical science could drive new advances in global health, therefore more training in technology is needed among health care workers. To assess the potential for informatics training using an approach designed to foster interaction at this interface, the University of Washington and the Universidad Peruana Cayetano Heredia developed and assessed a one-week course that included a new Bioinformatics (BIO) track along with an established Medical/Public Health Informatics track (MI) for participants in Peru. Methods We assessed the background of the participants, and measured the knowledge gained by track-specific (MI or BIO) 30-minute pre- and post-tests. Participants' attitudes were evaluated both by daily evaluations and by an end-course evaluation. Results Forty-three participants enrolled in the course – 20 in the MI track and 23 in the BIO track. Of 20 questions, the mean % score for the MI track increased from 49.7 pre-test (standard deviation or SD = 17.0) to 59.7 (SD = 15.2) for the post-test (P = 0.002, n = 18). The BIO track mean score increased from 33.6 pre-test to 51.2 post-test (P < 0.001, n = 21). Most comments (76%) about any aspect of the course were positive. The main perceived strength of the course was the quality of the speakers, and the main perceived weakness was the short duration of the course. Overall, the course acceptability was very good to excellent with a rating of 4.1 (scale 1–5), and the usefulness of the course was rated as very good. Most participants (62.9%) expressed a positive opinion about having had the BIO and MI tracks come together for some of the lectures. Conclusion Pre- and post-test results and the positive evaluations by the participants indicate that this first joint Bioinformatics and Medical/Public Health Informatics (MI and BIO) course was a success. PMID:18194533

Evaluation of a joint Bioinformatics and Medical Informatics international course in Peru.

PubMed

Curioso, Walter H; Hansen, Jacquelyn R; Centurion-Lara, Arturo; Garcia, Patricia J; Wolf, Fredric M; Fuller, Sherrilynne; Holmes, King K; Kimball, Ann Marie

2008-01-14

New technologies that emerge at the interface of computational and biomedical science could drive new advances in global health, therefore more training in technology is needed among health care workers. To assess the potential for informatics training using an approach designed to foster interaction at this interface, the University of Washington and the Universidad Peruana Cayetano Heredia developed and assessed a one-week course that included a new Bioinformatics (BIO) track along with an established Medical/Public Health Informatics track (MI) for participants in Peru. We assessed the background of the participants, and measured the knowledge gained by track-specific (MI or BIO) 30-minute pre- and post-tests. Participants' attitudes were evaluated both by daily evaluations and by an end-course evaluation. Forty-three participants enrolled in the course - 20 in the MI track and 23 in the BIO track. Of 20 questions, the mean % score for the MI track increased from 49.7 pre-test (standard deviation or SD = 17.0) to 59.7 (SD = 15.2) for the post-test (P = 0.002, n = 18). The BIO track mean score increased from 33.6 pre-test to 51.2 post-test (P < 0.001, n = 21). Most comments (76%) about any aspect of the course were positive. The main perceived strength of the course was the quality of the speakers, and the main perceived weakness was the short duration of the course. Overall, the course acceptability was very good to excellent with a rating of 4.1 (scale 1-5), and the usefulness of the course was rated as very good. Most participants (62.9%) expressed a positive opinion about having had the BIO and MI tracks come together for some of the lectures. Pre- and post-test results and the positive evaluations by the participants indicate that this first joint Bioinformatics and Medical/Public Health Informatics (MI and BIO) course was a success.

DisArticle: a web server for SVM-based discrimination of articles on traditional medicine.

PubMed

Kim, Sang-Kyun; Nam, SeJin; Kim, SangHyun

2017-01-28

Much research has been done in Northeast Asia to show the efficacy of traditional medicine. While MEDLINE contains many biomedical articles including those on traditional medicine, it does not categorize those articles by specific research area. The aim of this study was to provide a method that searches for articles only on traditional medicine in Northeast Asia, including traditional Chinese medicine, from among the articles in MEDLINE. This research established an SVM-based classifier model to identify articles on traditional medicine. The TAK + HM classifier, trained with the features of title, abstract, keywords, herbal data, and MeSH, has a precision of 0.954 and a recall of 0.902. In particular, the feature of herbal data significantly increased the performance of the classifier. By using the TAK + HM classifier, a total of about 108,000 articles were discriminated as articles on traditional medicine from among all articles in MEDLINE. We also built a web server called DisArticle ( http://informatics.kiom.re.kr/disarticle ), in which users can search for the articles and obtain statistical data. Because much evidence-based research on traditional medicine has been published in recent years, it has become necessary to search for articles on traditional medicine exclusively in literature databases. DisArticle can help users to search for and analyze the research trends in traditional medicine.

"Big data" and the electronic health record.

PubMed

Ross, M K; Wei, W; Ohno-Machado, L

2014-08-15

Implementation of Electronic Health Record (EHR) systems continues to expand. The massive number of patient encounters results in high amounts of stored data. Transforming clinical data into knowledge to improve patient care has been the goal of biomedical informatics professionals for many decades, and this work is now increasingly recognized outside our field. In reviewing the literature for the past three years, we focus on "big data" in the context of EHR systems and we report on some examples of how secondary use of data has been put into practice. We searched PubMed database for articles from January 1, 2011 to November 1, 2013. We initiated the search with keywords related to "big data" and EHR. We identified relevant articles and additional keywords from the retrieved articles were added. Based on the new keywords, more articles were retrieved and we manually narrowed down the set utilizing predefined inclusion and exclusion criteria. Our final review includes articles categorized into the themes of data mining (pharmacovigilance, phenotyping, natural language processing), data application and integration (clinical decision support, personal monitoring, social media), and privacy and security. The increasing adoption of EHR systems worldwide makes it possible to capture large amounts of clinical data. There is an increasing number of articles addressing the theme of "big data", and the concepts associated with these articles vary. The next step is to transform healthcare big data into actionable knowledge.

Molecular diversity management strategies for building and enhancement of diverse and focused lead discovery compound screening collections.

PubMed

Schuffenhauer, A; Popov, M; Schopfer, U; Acklin, P; Stanek, J; Jacoby, E

2004-12-01

This publication describes processes for the selection of chemical compounds for the building of a high-throughput screening (HTS) collection for drug discovery, using the currently implemented process in the Discovery Technologies Unit of the Novartis Institute for Biomedical Research, Basel Switzerland as reference. More generally, the currently existing compound acquisition models and practices are discussed. Our informatics, chemistry and biology-driven compound selection consists of two steps: 1) The individual compounds are filtered and grouped into three priority classes on the basis of their individual structural properties. Substructure filters are used to eliminate or penalize compounds based on unwanted structural properties. The similarity of the structures to reference ligands of the main proven druggable target families is computed, and drug-similar compounds are prioritized for the following diversity analysis. 2) The compounds are compared to the archive compounds and a diversity analysis is performed. This is done separately for the prioritized, regular and penalized compounds with increasingly stringent dissimilarity criterion. The process includes collecting vendor catalogues and monitoring the availability of samples together with the selection and purchase decision points. The development of a corporate vendor catalogue database is described. In addition to the selection methods on a per single molecule basis, selection criteria for scaffold and combinatorial chemistry projects in collaboration with compound vendors are discussed.

Bioinformatics Symposium of the Analytical Division of the American Chemical Society Meeting. Final Technical Report from 03/15/2000 to 03/14/2001 [sample pages of agenda, abstracts, index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kennedy, Robert T.

Sparked by the Human Genome Project, biological and biomedical research has become an information science. Information tools are now being generated for proteins, cell modeling, and genomics. The opportunity for analytical chemistry in this new environment is profound. New analytical techniques that can provide the information on genes, SNPs, proteins, protein modifications, cells, and cell chemistry are required. In this symposium, we brought together both informatics experts and leading analytical chemists to discuss this interface. Over 200 people attended this highly successful symposium.

Advanced Processing for Biomedical Informatics (APBI)

DTIC Science & Technology

2009-10-01

phosphatidic acid phosphatase type 2 domain containing 1A PPAPDC1A 1 96051 2.71E-06 4.39E-05 4.55 8.14 12.1 205030_at fatty acid binding protein 7...W81XWH‐06‐2‐0072    Principal Investigator: Craig D. Shriver, COL MC    54    209355_s_at phosphatidic acid phosphatase type 2B PPAP2B 8613 1.62E-06...Investigator: Craig D. Shriver, COL MC    24    209711_at solute carrier family 35 (UDP- glucuronic acid /UDP-N- acetylgalactosamine dual transporter), member

Ten quick tips for machine learning in computational biology.

PubMed

Chicco, Davide

2017-01-01

Machine learning has become a pivotal tool for many projects in computational biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical researchers often do not have enough experience to run a data mining project effectively, and therefore can follow incorrect practices, that may lead to common mistakes or over-optimistic results. With this review, we present ten quick tips to take advantage of machine learning in any computational biology context, by avoiding some common errors that we observed hundreds of times in multiple bioinformatics projects. We believe our ten suggestions can strongly help any machine learning practitioner to carry on a successful project in computational biology and related sciences.

The development of variable MLM editor and TSQL translator based on Arden Syntax in Taiwan.

PubMed

Liang, Yan Ching; Chang, Polun

2003-01-01

The Arden Syntax standard has been utilized in the medical informatics community in several countries during the past decade. It is never used in nursing in Taiwan. We try to develop a system that acquire medical expert knowledge in Chinese and translates data and logic slot into TSQL Language. The system implements TSQL translator interpreting database queries referred to in the knowledge modules. The decision-support systems in medicine are data driven system where TSQL triggers as inference engine can be used to facilitate linking to a database.

caGrid 1.0 : an enterprise Grid infrastructure for biomedical research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oster, S.; Langella, S.; Hastings, S.

To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research. Design: An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG{trademark}) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including (1) discovery, (2) integrated and large-scale data analysis, and (3) coordinated study. Measurements: The caGrid is built as a Grid software infrastructure andmore » leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications. Results: The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: .« less

Drug knowledge bases and their applications in biomedical informatics research.

PubMed

Zhu, Yongjun; Elemento, Olivier; Pathak, Jyotishman; Wang, Fei

2018-01-03

Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives have been taken to help researchers make good use of them. As the results of these initiatives, many drug knowledge bases have been constructed. They range from simple ones with specific focuses to comprehensive ones that contain information on almost every aspect of a drug. These curated drug knowledge bases have made significant contributions to the development of efficient and effective health information technologies for better health-care service delivery. Understanding and comparing existing drug knowledge bases and how they are applied in various biomedical studies will help us recognize the state of the art and design better knowledge bases in the future. In addition, researchers can get insights on novel applications of the drug knowledge bases through a review of successful use cases. In this study, we provide a review of existing popular drug knowledge bases and their applications in drug-related studies. We discuss challenges in constructing and using drug knowledge bases as well as future research directions toward a better ecosystem of drug knowledge bases. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Oxidative Lung Injury in Virus-Induced Wheezing

DTIC Science & Technology

2015-07-01

Biology (ASBMB) Annual meeting 2015 – Boston, MA, USA – Mar 30, 2015 b. Informatics such as databases and animal models, etc.: 1. We have generated a...manner. Mice were treated by gavage with 250 mg/kg body weight of BHA or corn oil (diluents for BHA) two days prior to RSV infection and during the first

Ontology based heterogeneous materials database integration and semantic query

NASA Astrophysics Data System (ADS)

Zhao, Shuai; Qian, Quan

2017-10-01

Materials digital data, high throughput experiments and high throughput computations are regarded as three key pillars of materials genome initiatives. With the fast growth of materials data, the integration and sharing of data is very urgent, that has gradually become a hot topic of materials informatics. Due to the lack of semantic description, it is difficult to integrate data deeply in semantic level when adopting the conventional heterogeneous database integration approaches such as federal database or data warehouse. In this paper, a semantic integration method is proposed to create the semantic ontology by extracting the database schema semi-automatically. Other heterogeneous databases are integrated to the ontology by means of relational algebra and the rooted graph. Based on integrated ontology, semantic query can be done using SPARQL. During the experiments, two world famous First Principle Computational databases, OQMD and Materials Project are used as the integration targets, which show the availability and effectiveness of our method.

Clique-based data mining for related genes in a biomedical database.

PubMed

Matsunaga, Tsutomu; Yonemori, Chikara; Tomita, Etsuji; Muramatsu, Masaaki

2009-07-01

Progress in the life sciences cannot be made without integrating biomedical knowledge on numerous genes in order to help formulate hypotheses on the genetic mechanisms behind various biological phenomena, including diseases. There is thus a strong need for a way to automatically and comprehensively search from biomedical databases for related genes, such as genes in the same families and genes encoding components of the same pathways. Here we address the extraction of related genes by searching for densely-connected subgraphs, which are modeled as cliques, in a biomedical relational graph. We constructed a graph whose nodes were gene or disease pages, and edges were the hyperlink connections between those pages in the Online Mendelian Inheritance in Man (OMIM) database. We obtained over 20,000 sets of related genes (called 'gene modules') by enumerating cliques computationally. The modules included genes in the same family, genes for proteins that form a complex, and genes for components of the same signaling pathway. The results of experiments using 'metabolic syndrome'-related gene modules show that the gene modules can be used to get a coherent holistic picture helpful for interpreting relations among genes. We presented a data mining approach extracting related genes by enumerating cliques. The extracted gene sets provide a holistic picture useful for comprehending complex disease mechanisms.

Big³. Editorial.

PubMed

Lehmann, C U; Séroussi, B; Jaulent, M-C

2014-05-22

To provide an editorial introduction into the 2014 IMIA Yearbook of Medical Informatics with an overview of the content, the new publishing scheme, and upcoming 25th anniversary. A brief overview of the 2014 special topic, Big Data - Smart Health Strategies, and an outline of the novel publishing model is provided in conjunction with a call for proposals to celebrate the 25th anniversary of the Yearbook. 'Big Data' has become the latest buzzword in informatics and promise new approaches and interventions that can improve health, well-being, and quality of life. This edition of the Yearbook acknowledges the fact that we just started to explore the opportunities that 'Big Data' will bring. However, it will become apparent to the reader that its pervasive nature has invaded all aspects of biomedical informatics - some to a higher degree than others. It was our goal to provide a comprehensive view at the state of 'Big Data' today, explore its strengths and weaknesses, as well as its risks, discuss emerging trends, tools, and applications, and stimulate the development of the field through the aggregation of excellent survey papers and working group contributions to the topic. For the first time in history will the IMIA Yearbook be published in an open access online format allowing a broader readership especially in resource poor countries. For the first time, thanks to the online format, will the IMIA Yearbook be published twice in the year, with two different tracks of papers. We anticipate that the important role of the IMIA yearbook will further increase with these changes just in time for its 25th anniversary in 2016.

A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis.

PubMed

Kim, Seongsoon; Park, Donghyeon; Choi, Yonghwa; Lee, Kyubum; Kim, Byounggun; Jeon, Minji; Kim, Jihye; Tan, Aik Choon; Kang, Jaewoo

2018-01-05

With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since there is no dataset for the biomedical literature comprehension task, our work includes generating a large-scale question answering dataset using PubMed and manually evaluating the generated dataset. We present an attention-based deep neural model tailored to the biomedical domain. To further enhance the performance of our model, we used a pretrained word vector and biomedical entity type embedding. We also developed an ensemble method of combining the results of several independent models to reduce the variance of the answers from the models. The experimental results showed that our proposed deep neural network model outperformed the baseline model by more than 7% on the new dataset. We also evaluated human performance on the new dataset. The human evaluation result showed that our deep neural model outperformed humans in comprehension by 22% on average. In this work, we introduced a new task of machine comprehension in the biomedical domain using a deep neural model. Since there was no large-scale dataset for training deep neural models in the biomedical domain, we created the new cloze-style datasets Biomedical Knowledge Comprehension Title (BMKC_T) and Biomedical Knowledge Comprehension Last Sentence (BMKC_LS) (together referred to as BioMedical Knowledge Comprehension) using the PubMed corpus. The experimental results showed that the performance of our model is much higher than that of humans. We observed that our model performed consistently better regardless of the degree of difficulty of a text, whereas humans have difficulty when performing biomedical literature comprehension tasks that require expert level knowledge. ©Seongsoon Kim, Donghyeon Park, Yonghwa Choi, Kyubum Lee, Byounggun Kim, Minji Jeon, Jihye Kim, Aik Choon Tan, Jaewoo Kang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.01.2018.

Information revolution in nursing and health care: educating for tomorrow's challenge.

PubMed

Kooker, B M; Richardson, S S

1994-06-01

Current emphasis on the national electronic highway and a national health database for comparative health care reporting demonstrates society's increasing reliance on information technology. The efficient electronic processing and managing of data, information, and knowledge are critical for survival in tomorrow's health care organization. To take a leadership role in this information revolution, informatics nurse specialists must possess competencies that incorporate information science, computer science, and nursing science for successful information system development. In selecting an appropriate informatics educational program or to hire an individual capable of meeting this challenge, nurse administrators must look for the following technical knowledge and skill set: information management principles, system development life cycle, programming languages, file design and access, hardware and network architecture, project management skills, and leadership abilities.

Biomedical databases: protecting privacy and promoting research.

PubMed

Wylie, Jean E; Mineau, Geraldine P

2003-03-01

When combined with medical information, large electronic databases of information that identify individuals provide superlative resources for genetic, epidemiology and other biomedical research. Such research resources increasingly need to balance the protection of privacy and confidentiality with the promotion of research. Models that do not allow the use of such individual-identifying information constrain research; models that involve commercial interests raise concerns about what type of access is acceptable. Researchers, individuals representing the public interest and those developing regulatory guidelines must be involved in an ongoing dialogue to identify practical models.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference.

PubMed

Widdows, Dominic; Cohen, Trevor

2015-10-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.

Development of an informatics infrastructure for data exchange of biomolecular simulations: architecture, data models and ontology$

PubMed Central

Thibault, J. C.; Roe, D. R.; Eilbeck, K.; Cheatham, T. E.; Facelli, J. C.

2015-01-01

Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data – both within the same organization and among different ones – remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations. PMID:26387907

Past and next 10 years of medical informatics.

PubMed

Ückert, Frank; Ammenwerth, Elske; Dujat, Carl; Grant, Andrew; Haux, Reinhold; Hein, Andreas; Hochlehnert, Achim; Knaup-Gregori, Petra; Kulikowski, Casimir; Mantas, John; Maojo, Victor; Marschollek, Michael; Moura, Lincoln; Plischke, Maik; Röhrig, Rainer; Stausberg, Jürgen; Takabayashi, Katsuhiko; Winter, Alfred; Wolf, Klaus-Hendrik; Hasman, Arie

2014-07-01

More than 10 years ago Haux et al. tried to answer the question how health care provision will look like in the year 2013. A follow-up workshop was held in Braunschweig, Germany, for 2 days in May, 2013, with 20 invited international experts in biomedical and health informatics. Among other things it had the objectives to discuss the suggested goals and measures of 2002 and how priorities on MI research in this context should be set from the viewpoint of today. The goals from 2002 are now as up-to-date as they were then. The experts stated that the three goals: "patient-centred recording and use of medical data for cooperative care"; "process-integrated decision support through current medical knowledge" and "comprehensive use of patient data for research and health care reporting" have not been reached yet and are still relevant. A new goal for ICT in health care should be the support of patient centred personalized (individual) medicine. MI as an academic discipline carries out research concerning tools that support health care professionals in their work. This research should be carried out without the pressure that it should lead to systems that are immediately and directly accepted in practice.

Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

PubMed

Thibault, J C; Roe, D R; Eilbeck, K; Cheatham, T E; Facelli, J C

2015-01-01

Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data - both within the same organization and among different ones - remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference

PubMed Central

Widdows, Dominic; Cohen, Trevor

2015-01-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.1 PMID:26582967

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse.

PubMed

Eppig, Janan T

2017-07-01

The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided. © The Author 2017. Published by Oxford University Press.

Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse

PubMed Central

Eppig, Janan T.

2017-01-01

Abstract The Mouse Genome Informatics (MGI) Resource supports basic, translational, and computational research by providing high-quality, integrated data on the genetics, genomics, and biology of the laboratory mouse. MGI serves a strategic role for the scientific community in facilitating biomedical, experimental, and computational studies investigating the genetics and processes of diseases and enabling the development and testing of new disease models and therapeutic interventions. This review describes the nexus of the body of growing genetic and biological data and the advances in computer technology in the late 1980s, including the World Wide Web, that together launched the beginnings of MGI. MGI develops and maintains a gold-standard resource that reflects the current state of knowledge, provides semantic and contextual data integration that fosters hypothesis testing, continually develops new and improved tools for searching and analysis, and partners with the scientific community to assure research data needs are met. Here we describe one slice of MGI relating to the development of community-wide large-scale mutagenesis and phenotyping projects and introduce ways to access and use these MGI data. References and links to additional MGI aspects are provided. PMID:28838066

Consensus-Driven Development of a Terminology for Biobanking, the Duke Experience.

PubMed

Ellis, Helena; Joshi, Mary-Beth; Lynn, Aenoch J; Walden, Anita

2017-04-01

Biobanking at Duke University has existed for decades and has grown over time in silos and based on specialized needs, as is true with most biomedical research centers. These silos developed informatics systems to support their own individual requirements, with no regard for semantic or syntactic interoperability. Duke undertook an initiative to implement an enterprise-wide biobanking information system to serve its many diverse biobanking entities. A significant part of this initiative was the development of a common terminology for use in the commercial software platform. Common terminology provides the foundation for interoperability across biobanks for data and information sharing. We engaged experts in research, informatics, and biobanking through a consensus-driven process to agree on 361 terms and their definitions that encompass the lifecycle of a biospecimen. Existing standards, common terms, and data elements from published articles provided a foundation on which to build the biobanking terminology; a broader set of stakeholders then provided additional input and feedback in a secondary vetting process. The resulting standardized biobanking terminology is now available for sharing with the biobanking community to serve as a foundation for other institutions who are considering a similar initiative.

Consensus-Driven Development of a Terminology for Biobanking, the Duke Experience

PubMed Central

Joshi, Mary-Beth; Lynn, Aenoch J.; Walden, Anita

2017-01-01

Biobanking at Duke University has existed for decades and has grown over time in silos and based on specialized needs, as is true with most biomedical research centers. These silos developed informatics systems to support their own individual requirements, with no regard for semantic or syntactic interoperability. Duke undertook an initiative to implement an enterprise-wide biobanking information system to serve its many diverse biobanking entities. A significant part of this initiative was the development of a common terminology for use in the commercial software platform. Common terminology provides the foundation for interoperability across biobanks for data and information sharing. We engaged experts in research, informatics, and biobanking through a consensus-driven process to agree on 361 terms and their definitions that encompass the lifecycle of a biospecimen. Existing standards, common terms, and data elements from published articles provided a foundation on which to build the biobanking terminology; a broader set of stakeholders then provided additional input and feedback in a secondary vetting process. The resulting standardized biobanking terminology is now available for sharing with the biobanking community to serve as a foundation for other institutions who are considering a similar initiative. PMID:28338350

Informatics and machine learning to define the phenotype.

PubMed

Basile, Anna Okula; Ritchie, Marylyn DeRiggi

2018-03-01

For the past decade, the focus of complex disease research has been the genotype. From technological advancements to the development of analysis methods, great progress has been made. However, advances in our definition of the phenotype have remained stagnant. Phenotype characterization has recently emerged as an exciting area of informatics and machine learning. The copious amounts of diverse biomedical data that have been collected may be leveraged with data-driven approaches to elucidate trait-related features and patterns. Areas covered: In this review, the authors discuss the phenotype in traditional genetic associations and the challenges this has imposed.Approaches for phenotype refinement that can aid in more accurate characterization of traits are also discussed. Further, the authors highlight promising machine learning approaches for establishing a phenotype and the challenges of electronic health record (EHR)-derived data. Expert commentary: The authors hypothesize that through unsupervised machine learning, data-driven approaches can be used to define phenotypes rather than relying on expert clinician knowledge. Through the use of machine learning and an unbiased set of features extracted from clinical repositories, researchers will have the potential to further understand complex traits and identify patient subgroups. This knowledge may lead to more preventative and precise clinical care.

Architecture for biomedical multimedia information delivery on the World Wide Web

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Goh, Gin-Hua; Neve, Leif; Thoma, George R.

1997-10-01

Research engineers at the National Library of Medicine are building a prototype system for the delivery of multimedia biomedical information on the World Wide Web. This paper discuses the architecture and design considerations for the system, which will be used initially to make images and text from the third National Health and Nutrition Examination Survey (NHANES) publicly available. We categorized our analysis as follows: (1) fundamental software tools: we analyzed trade-offs among use of conventional HTML/CGI, X Window Broadway, and Java; (2) image delivery: we examined the use of unconventional TCP transmission methods; (3) database manager and database design: we discuss the capabilities and planned use of the Informix object-relational database manager and the planned schema for the HNANES database; (4) storage requirements for our Sun server; (5) user interface considerations; (6) the compatibility of the system with other standard research and analysis tools; (7) image display: we discuss considerations for consistent image display for end users. Finally, we discuss the scalability of the system in terms of incorporating larger or more databases of similar data, and the extendibility of the system for supporting content-based retrieval of biomedical images. The system prototype is called the Web-based Medical Information Retrieval System. An early version was built as a Java applet and tested on Unix, PC, and Macintosh platforms. This prototype used the MiniSQL database manager to do text queries on a small database of records of participants in the second NHANES survey. The full records and associated x-ray images were retrievable and displayable on a standard Web browser. A second version has now been built, also a Java applet, using the MySQL database manager.

A Bioinformatics Module for Use in an Introductory Biology Laboratory

ERIC Educational Resources Information Center

Alaie, Adrienne; Teller, Virginia; Qiu, Wei-gang

2012-01-01

Since biomedical science has become increasingly data-intensive, acquisition of computational and quantitative skills by science students has become more important. For non-science students, an introduction to biomedical databases and their applications promotes the development of a scientifically literate population. Because typical college…

Comprehensive Environmental Informatics System (CEIS) Integrating Crew and Vehicle Environmental Health

NASA Technical Reports Server (NTRS)

Nall, Mark E.

2006-01-01

Integrated Vehicle Health Management (IVHM) systems have been pursued as highly integrated systems that include smart sensors, diagnostic and prognostics software for assessments of real-time and life-cycle vehicle health information. Inclusive to such a system is the requirement to monitor the environmental health within the vehicle and the occupants of the vehicle. In this regard an enterprise approach to informatics is used to develop a methodology entitled, Comprehensive Environmental Informatics System (CEIS). The hardware and software technologies integrated into this system will be embedded in the vehicle subsystems, and maintenance operations, to provide both real-time and life-cycle health information of the environment within the vehicle cabin and of its occupants. This comprehensive information database will enable informed decision making and logistics management. One key element of the CEIS is interoperability for data acquisition and archive between environment and human system monitoring. With comprehensive components the data acquired in this system will use model based reasoning systems for subsystem and system level managers, advanced on-board and ground-based mission and maintenance planners to assess system functionality. Knowledge databases of the vehicle health state will be continuously updated and reported for critical failure modes, and routinely updated and reported for life cycle condition trending. Sufficient intelligence, including evidence-based engineering practices which are analogous to evidencebased medicine practices, will be included in the CEIS to result in more rapid recognition of off-nominal operation to enable quicker corrective actions. This will result from better information (rather than just data) for improved crew/operator situational awareness, which will produce significant vehicle and crew safety improvements, as well as increasing the chance for mission success, future mission planning as well as training. Other benefits include improved reliability, increase safety in operations and cost of operations. The cost benefits stem from significantly reduced processing and operations manpower, predictive maintenance for systems and subjects. The improvements in vehicle functionality and cost will result from increased prognostic and diagnostic capability due to the detailed total human exploration system health knowledge from CEIS. A collateral benefit is that there will be closer observations of the vehicle occupants as wrist watch sized devices are worn for continuous health monitoring. Additional database acquisition will stem from activities in countermeasure practices to ensure peak performance capability by occupants of the vehicle. The CEIS will provide data from advanced sensing technologies and informatics modeling which will be useful in problem troubleshooting, and improving NASA s awareness of systems during operation.

The porcine translational research database: A manually curated, genomics and proteomics-based research resource

USDA-ARS?s Scientific Manuscript database

The use of swine in biomedical research has increased dramatically in the last decade. Diverse genomic- and proteomic databases have been developed to facilitate research using human and rodent models. Current porcine gene databases, however, lack the robust annotation to study pig models that are...

[Application of the life sciences platform based on oracle to biomedical informations].

PubMed

Zhao, Zhi-Yun; Li, Tai-Huan; Yang, Hong-Qiao

2008-03-01

The life sciences platform based on Oracle database technology is introduced in this paper. By providing a powerful data access, integrating a variety of data types, and managing vast quantities of data, the software presents a flexible, safe and scalable management platform for biomedical data processing.

Development of a Web-Enabled Informatics Platform for Manipulation of Gene Expression Data

DTIC Science & Technology

2004-12-01

genomic platforms such as metabolomics and proteomics , and to federated databases for knowledge management. A successful SBIR Phase I completed...measurements that require sophisticated bioinformatic platforms for data archival, management, integration, and analysis if researchers are to derive...web-enabled bioinformatic platform consisting of a Laboratory Information Management System (LIMS), an Analysis Information Management System (AIMS

Greater physician involvement improves coding outcomes in endobronchial ultrasound-guided transbronchial needle aspiration procedures.

PubMed

Pillai, Anilkumar; Medford, Andrew R L

2013-01-01

Correct coding is essential for accurate reimbursement for clinical activity. Published data confirm that significant aberrations in coding occur, leading to considerable financial inaccuracies especially in interventional procedures such as endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). Previous data reported a 15% coding error for EBUS-TBNA in a U.K. service. We hypothesised that greater physician involvement with coders would reduce EBUS-TBNA coding errors and financial disparity. The study was done as a prospective cohort study in the tertiary EBUS-TBNA service in Bristol. 165 consecutive patients between October 2009 and March 2012 underwent EBUS-TBNA for evaluation of unexplained mediastinal adenopathy on computed tomography. The chief coder was prospectively electronically informed of all procedures and cross-checked on a prospective database and by Trust Informatics. Cost and coding analysis was performed using the 2010-2011 tariffs. All 165 procedures (100%) were coded correctly as verified by Trust Informatics. This compares favourably with the 14.4% coding inaccuracy rate for EBUS-TBNA in a previous U.K. prospective cohort study [odds ratio 201.1 (1.1-357.5), p = 0.006]. Projected income loss was GBP 40,000 per year in the previous study, compared to a GBP 492,195 income here with no coding-attributable loss in revenue. Greater physician engagement with coders prevents coding errors and financial losses which can be significant especially in interventional specialties. The intervention can be as cheap, quick and simple as a prospective email to the coding team with cross-checks by Trust Informatics and against a procedural database. We suggest that all specialties should engage more with their coders using such a simple intervention to prevent revenue losses. Copyright © 2013 S. Karger AG, Basel.

Online molecular image repository and analysis system: A multicenter collaborative open-source infrastructure for molecular imaging research and application.

PubMed

Rahman, Mahabubur; Watabe, Hiroshi

2018-05-01

Molecular imaging serves as an important tool for researchers and clinicians to visualize and investigate complex biochemical phenomena using specialized instruments; these instruments are either used individually or in combination with targeted imaging agents to obtain images related to specific diseases with high sensitivity, specificity, and signal-to-noise ratios. However, molecular imaging, which is a multidisciplinary research field, faces several challenges, including the integration of imaging informatics with bioinformatics and medical informatics, requirement of reliable and robust image analysis algorithms, effective quality control of imaging facilities, and those related to individualized disease mapping, data sharing, software architecture, and knowledge management. As a cost-effective and open-source approach to address these challenges related to molecular imaging, we develop a flexible, transparent, and secure infrastructure, named MIRA, which stands for Molecular Imaging Repository and Analysis, primarily using the Python programming language, and a MySQL relational database system deployed on a Linux server. MIRA is designed with a centralized image archiving infrastructure and information database so that a multicenter collaborative informatics platform can be built. The capability of dealing with metadata, image file format normalization, and storing and viewing different types of documents and multimedia files make MIRA considerably flexible. With features like logging, auditing, commenting, sharing, and searching, MIRA is useful as an Electronic Laboratory Notebook for effective knowledge management. In addition, the centralized approach for MIRA facilitates on-the-fly access to all its features remotely through any web browser. Furthermore, the open-source approach provides the opportunity for sustainable continued development. MIRA offers an infrastructure that can be used as cross-boundary collaborative MI research platform for the rapid achievement in cancer diagnosis and therapeutics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

PubMed Central

SHARMA, ANKIT; GHATGE, MADANKUMAR; MUNDKUR, LAKSHMI; VANGALA, RAJANI KANTH

2016-01-01

Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD-gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)-induced genes were identified from the literature and the CAD-associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identifed in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ-glutamyl transferase (GGT)-5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV-neutralizing antibody (CMV-NA) titers. The C-statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

Constructing a Graph Database for Semantic Literature-Based Discovery.

PubMed

Hristovski, Dimitar; Kastrin, Andrej; Dinevski, Dejan; Rindflesch, Thomas C

2015-01-01

Literature-based discovery (LBD) generates discoveries, or hypotheses, by combining what is already known in the literature. Potential discoveries have the form of relations between biomedical concepts; for example, a drug may be determined to treat a disease other than the one for which it was intended. LBD views the knowledge in a domain as a network; a set of concepts along with the relations between them. As a starting point, we used SemMedDB, a database of semantic relations between biomedical concepts extracted with SemRep from Medline. SemMedDB is distributed as a MySQL relational database, which has some problems when dealing with network data. We transformed and uploaded SemMedDB into the Neo4j graph database, and implemented the basic LBD discovery algorithms with the Cypher query language. We conclude that storing the data needed for semantic LBD is more natural in a graph database. Also, implementing LBD discovery algorithms is conceptually simpler with a graph query language when compared with standard SQL.

Information-seeking behavior and the use of online resources: a snapshot of current health sciences faculty.

PubMed

De Groote, Sandra L; Shultz, Mary; Blecic, Deborah D

2014-07-01

The research assesses the information-seeking behaviors of health sciences faculty, including their use of online databases, journals, and social media. A survey was designed and distributed via email to 754 health sciences faculty at a large urban research university with 6 health sciences colleges. Twenty-six percent (198) of faculty responded. MEDLINE was the primary database utilized, with 78.5% respondents indicating they use the database at least once a week. Compared to MEDLINE, Google was utilized more often on a daily basis. Other databases showed much lower usage. Low use of online databases other than MEDLINE, link-out tools to online journals, and online social media and collaboration tools demonstrates a need for meaningful promotion of online resources and informatics literacy instruction for faculty. Library resources are plentiful and perhaps somewhat overwhelming. Librarians need to help faculty discover and utilize the resources and tools that libraries have to offer.

The Development of Variable MLM Editor and TSQL Translator Based on Arden Syntax in Taiwan

PubMed Central

Liang, Yan-Ching; Chang, Polun

2003-01-01

The Arden Syntax standard has been utilized in the medical informatics community in several countries during the past decade. It is never used in nursing in Taiwan. We try to develop a system that acquire medical expert knowledge in Chinese and translates data and logic slot into TSQL Language. The system implements TSQL translator interpreting database queries referred to in the knowledge modules. The decision-support systems in medicine are data driven system where TSQL triggers as inference engine can be used to facilitate linking to a database. PMID:14728414

How Sensor, Signal, and Imaging Informatics May Impact Patient Centered Care and Care Coordination

PubMed Central

Moreau-Gaudry, A.

2015-01-01

Summary Objective This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2015 of excellent research in the broad field of Sensor, Signal, and Imaging Informatics published in the year 2014, with a focus on patient centered care coordination. Methods The two section editors performed a systematic initial selection and a double blind peer review process to select a list of candidate best papers in the domain published in 2014, from the PubMed and Web of Science databases. A set of MeSH keywords provided by experts was used. This selection was peer-reviewed by external reviewers. Results The review process highlighted articles illustrating two current trends related to care coordination and patient centered care: the enhanced capacity to predict the evolution of a disease based on patient-specific information can impact care coordination; similarly, better perception of the patient and his treatment could lead to enhanced personalized care with a potential impact on care coordination. Conclusions This review shows the multiplicity of angles from which the question of patient-centered care can be addressed, with consequences on care coordination that will need to be confirmed and demonstrated in the future. PMID:26293856

caNanoLab: data sharing to expedite the use of nanotechnology in biomedicine

PubMed Central

Gaheen, Sharon; Hinkal, George W.; Morris, Stephanie A.; Lijowski, Michal; Heiskanen, Mervi

2014-01-01

The use of nanotechnology in biomedicine involves the engineering of nanomaterials to act as therapeutic carriers, targeting agents and diagnostic imaging devices. The application of nanotechnology in cancer aims to transform early detection, targeted therapeutics and cancer prevention and control. To assist in expediting and validating the use of nanomaterials in biomedicine, the National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology, in collaboration with the NCI Alliance for Nanotechnology in Cancer (Alliance), has developed a data sharing portal called caNanoLab. caNanoLab provides access to experimental and literature curated data from the NCI Nanotechnology Characterization Laboratory, the Alliance and the greater cancer nanotechnology community. PMID:25364375

Heterogeneous data fusion for brain tumor classification.

PubMed

Metsis, Vangelis; Huang, Heng; Andronesi, Ovidiu C; Makedon, Fillia; Tzika, Aria

2012-10-01

Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this report, we present a novel machine learning framework for brain tumor classification based on heterogeneous data fusion of metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) magnetic resonance spectroscopy and gene transcriptome profiling, obtained from intact brain tumor biopsies. Our experimental results show that our novel framework outperforms any analysis using individual dataset.

Combining clinical and genomics queries using i2b2 – Three methods

PubMed Central

Murphy, Shawn N.; Avillach, Paul; Bellazzi, Riccardo; Phillips, Lori; Gabetta, Matteo; Eran, Alal; McDuffie, Michael T.; Kohane, Isaac S.

2017-01-01

We are fortunate to be living in an era of twin biomedical data surges: a burgeoning representation of human phenotypes in the medical records of our healthcare systems, and high-throughput sequencing making rapid technological advances. The difficulty representing genomic data and its annotations has almost by itself led to the recognition of a biomedical “Big Data” challenge, and the complexity of healthcare data only compounds the problem to the point that coherent representation of both systems on the same platform seems insuperably difficult. We investigated the capability for complex, integrative genomic and clinical queries to be supported in the Informatics for Integrating Biology and the Bedside (i2b2) translational software package. Three different data integration approaches were developed: The first is based on Sequence Ontology, the second is based on the tranSMART engine, and the third on CouchDB. These novel methods for representing and querying complex genomic and clinical data on the i2b2 platform are available today for advancing precision medicine. PMID:28388645

Ambient intelligence for monitoring and research in clinical neurophysiology and medicine: the MIMERICA* project and prototype.

PubMed

Pignolo, L; Riganello, F; Dolce, G; Sannita, W G

2013-04-01

Ambient Intelligence (AmI) provides extended but unobtrusive sensing and computing devices and ubiquitous networking for human/environment interaction. It is a new paradigm in information technology compliant with the international Integrating Healthcare Enterprise board (IHE) and eHealth HL7 technological standards in the functional integration of biomedical domotics and informatics in hospital and home care. AmI allows real-time automatic recording of biological/medical information and environmental data. It is extensively applicable to patient monitoring, medicine and neuroscience research, which require large biomedical data sets; for example, in the study of spontaneous or condition-dependent variability or chronobiology. In this respect, AML is equivalent to a traditional laboratory for data collection and processing, with minimal dedicated equipment, staff, and costs; it benefits from the integration of artificial intelligence technology with traditional/innovative sensors to monitor clinical or functional parameters. A prototype AmI platform (MIMERICA*) has been implemented and is operated in a semi-intensive unit for the vegetative and minimally conscious states, to investigate the spontaneous or environment-related fluctuations of physiological parameters in these conditions.

Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

PubMed

Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E

2014-01-01

The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.

Developing Cancer Informatics Applications and Tools Using the NCI Genomic Data Commons API.

PubMed

Wilson, Shane; Fitzsimons, Michael; Ferguson, Martin; Heath, Allison; Jensen, Mark; Miller, Josh; Murphy, Mark W; Porter, James; Sahni, Himanso; Staudt, Louis; Tang, Yajing; Wang, Zhining; Yu, Christine; Zhang, Junjun; Ferretti, Vincent; Grossman, Robert L

2017-11-01

The NCI Genomic Data Commons (GDC) was launched in 2016 and makes available over 4 petabytes (PB) of cancer genomic and associated clinical data to the research community. This dataset continues to grow and currently includes over 14,500 patients. The GDC is an example of a biomedical data commons, which collocates biomedical data with storage and computing infrastructure and commonly used web services, software applications, and tools to create a secure, interoperable, and extensible resource for researchers. The GDC is (i) a data repository for downloading data that have been submitted to it, and also a system that (ii) applies a common set of bioinformatics pipelines to submitted data; (iii) reanalyzes existing data when new pipelines are developed; and (iv) allows users to build their own applications and systems that interoperate with the GDC using the GDC Application Programming Interface (API). We describe the GDC API and how it has been used both by the GDC itself and by third parties. Cancer Res; 77(21); e15-18. ©2017 AACR . ©2017 American Association for Cancer Research.

The BiolAD-DB system : an informatics system for clinical and genetic data.

PubMed

Nielsen, David A; Leidner, Marty; Haynes, Chad; Krauthammer, Michael; Kreek, Mary Jeanne

2007-01-01

The Biology of Addictive Diseases-Database (BiolAD-DB) system is a research bioinformatics system for archiving, analyzing, and processing of complex clinical and genetic data. The database schema employs design principles for handling complex clinical information, such as response items in genetic questionnaires. Data access and validation is provided by the BiolAD-DB client application, which features a data validation engine tightly coupled to a graphical user interface. Data integrity is provided by the password-protected BiolAD-DB SQL compliant server and database. BiolAD-DB tools further provide functionalities for generating customized reports and views. The BiolAD-DB system schema, client, and installation instructions are freely available at http://www.rockefeller.edu/biolad-db/.

Olelo: a web application for intuitive exploration of biomedical literature

PubMed Central

Niedermeier, Julian; Jankrift, Marcel; Tietböhl, Sören; Stachewicz, Toni; Folkerts, Hendrik; Uflacker, Matthias; Neves, Mariana

2017-01-01

Abstract Researchers usually query the large biomedical literature in PubMed via keywords, logical operators and filters, none of which is very intuitive. Question answering systems are an alternative to keyword searches. They allow questions in natural language as input and results reflect the given type of question, such as short answers and summaries. Few of those systems are available online but they experience drawbacks in terms of long response times and they support a limited amount of question and result types. Additionally, user interfaces are usually restricted to only displaying the retrieved information. For our Olelo web application, we combined biomedical literature and terminologies in a fast in-memory database to enable real-time responses to researchers’ queries. Further, we extended the built-in natural language processing features of the database with question answering and summarization procedures. Combined with a new explorative approach of document filtering and a clean user interface, Olelo enables a fast and intelligent search through the ever-growing biomedical literature. Olelo is available at http://www.hpi.de/plattner/olelo. PMID:28472397