Opportunities and obstacles for deep learning in biology and medicine

Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex...

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Bibliographic Details
Published in:	Journal of the Royal Society interface Vol. 15; no. 141
Main Authors:	Ching, Travers, Himmelstein, Daniel S, Beaulieu-Jones, Brett K, Kalinin, Alexandr A, Do, Brian T, Way, Gregory P, Ferrero, Enrico, Agapow, Paul-Michael, Zietz, Michael, Hoffman, Michael M, Xie, Wei, Rosen, Gail L, Lengerich, Benjamin J, Israeli, Johnny, Lanchantin, Jack, Woloszynek, Stephen, Carpenter, Anne E, Shrikumar, Avanti, Xu, Jinbo, Cofer, Evan M, Lavender, Christopher A, Turaga, Srinivas C, Alexandari, Amr M, Lu, Zhiyong, Harris, David J, DeCaprio, Dave, Qi, Yanjun, Kundaje, Anshul, Peng, Yifan, Wiley, Laura K, Segler, Marwin H S, Boca, Simina M, Swamidass, S Joshua, Huang, Austin, Gitter, Anthony, Greene, Casey S
Format:	Journal Article
Language:	English
Published:	England 01.04.2018
Subjects:	Algorithms Biomedical Research - methods Biomedical Research - trends Biomedical Technology - trends Decision Making Deep Learning - trends Delivery of Health Care - methods Delivery of Health Care - trends Disease - genetics Drug Design Electronic Health Records - trends Humans Terminology as Topic deep learning genomics precision medicine machine learning
ISSN:	1742-5662, 1742-5662
Online Access:	Get more information
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