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Title Data science, learning and applications to biomedical and health sciences / editor, Nabil R. Adam, Rutgers, The State University of New Jersey
Imprint Hoboken, N.J. : Published on behalf of the New York Academy of Sciences by Wiley Subscription Services, Inc., a Wiley Company, [2017]
Descript 1 online resource (165 pages) : illustrations (some colour), map
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series Annals of the New York Academy of Sciences ; v. 1387
Annals of the New York Academy of Sciences ; v. 1387
Note Includes bibliographical references
Data science, learning, and applications to biomedical and health sciences / Nabil R. Adam, Robert Wieder and Debopriya Ghosh -- Introducing the Big Knowledge to Use (BK2U) challenge / Yehoshua Perl, James Geller, Michael Halper, Christopher Ochs, Ling Zheng and Joan Kapusnik-Uner -- Advanced literature analysis in a Big Data world / Chris Cheadle, Hongbao Cao, Andrey Kalinin and Jaqui Hodgkinson -- Correlating eligibility criteria generalizability and adverse events using Big Data for patients and clinical trials / Anando Sen, Patrick B. Ryan, Andrew Goldstein, Shreya Chakrabarti, Shuang Wang, Eileen Koski and Chunhua Weng -- PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data / Arash Shaban-Nejad, Maxime Lavigne, Anya Okhmatovskaia and David L. Buckeridge -- A vision for collaborative training infrastructure for bioinformatics / Jason J. Williams and Tracy K. Teal -- An overview of human genetic privacy / Xinghua Shi and Xintao Wu -- Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States / Shuang Wang, Xiaoqian Jiang, Siddharth Singh, Rebecca Marmor, Luca Bonomi, Dov Fox, Michelle Dow and Lucila Ohno-Machado -- Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study / Qiongge Li and Maria F. Chan -- Extension of research data repository system to support direct compute access to biomedical datasets: enhancing Dataverse to support large datasets / Bill McKinney, Peter A. Meyer, MercÃ̈ Crosas and Piotr Sliz -- Distributed data networks: a blueprint for Big Data sharing and healthcare analytics / Jennifer R. Popovic -- Big Data access and infrastructure for modern biology: case studies in data repository utility / Nathan C. Boles, Tyler Stone, Charles Bergeron and Thomas R. Kiehl -- Evolvix BEST Names for semantic reproducibility across code2brain interfaces / Laurence Loewe, Katherine S. Scheuer, Seth A. Keel, Vaibhav Vyas, Ben Liblit, Bret Hanlon, Michael C. Ferris, John Yin, Inês Dutra, Anthony Pietsch, Christine G. Javid, Cecilia L. Moog, Jocelyn Meyer, Jerdon Dresel, Brian McLoone, Sonya Loberger, Arezoo Movaghar, Morgaine Gilchrist-Scott, Yazeed Sabri, Dave Sescleifer, Ivan Pereda-Zorrilla, Andrew Zietlow, Rodrigo Smith, Samantha Pietenpol, Jacob Goldfinger, Sarah L. Atzen, Erika Freiberg, Noah P. Waters, Claire Nusbaum, Erik Nolan, Alyssa Hotz, Richard M. Kliman, Ayalew Mentewab, Nathan Fregien and Martha Loewe -- Video-based eye tracking for neuropsychiatric assessment / Sam Adhikari and David E. Stark -- Machine learning approaches to personalize early prediction of asthma exacerbations / Joseph Finkelstein and In cheol Jeong
"The last decade has seen an unprecedented increase in the volume and variety of electronic data related to research and development, health records, and patient self-tracking, collectively referred to as Big Data. Properly harnessed, Big Data can provide insights and drive discovery that will accelerate biomedical advances, improve patient outcomes, and reduce costs. However, the considerable potential of Big Data remains unrealized owing to obstacles including a limited ability to standardize and consolidate data and challenges in sharing data, among a variety of sources, providers, and facilities. Papers in this special issue discuss some of these challenges and potential solutions, as well as initiatives that are already underway to take advantage of Big Data."--Publisher's website
Subject Medical informatics
Medicine -- Data processing
Medicine -- Data processing -- Evaluation
Medicine -- Data processing -- Technological innovations
Medical records -- Data processing
Clinical medicine -- Data processing
Clinical medicine -- Decision making -- Data processing
Information storage and retrieval systems -- Medicine
Information storage and retrieval systems -- Medical care
Alt Author Adam, Nabil R., editor
New York Academy of Sciences, issuing body
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