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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Veröffentlicht in:	Journal of the Royal Society interface Jg. 15; H. 141
Hauptverfasser:	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
Sprache:	Englisch
Veröffentlicht:	England 01.04.2018
Schlagworte:	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-Zugang:	Weitere Angaben
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