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Nat Med. 2019 Jan;25(1):24-29. doi: 10.1038/s41591-018-0316-z. Epub 2019 Jan 7.

A guide to deep learning in healthcare.

Author information

1
Stanford University, Stanford, CA, USA. andre.esteva@gmail.com.
2
Stanford University, Stanford, CA, USA.
3
Google Research, San Jose, CA, USA.

Abstract

Here we present deep-learning techniques for healthcare, centering our discussion on deep learning in computer vision, natural language processing, reinforcement learning, and generalized methods. We describe how these computational techniques can impact a few key areas of medicine and explore how to build end-to-end systems. Our discussion of computer vision focuses largely on medical imaging, and we describe the application of natural language processing to domains such as electronic health record data. Similarly, reinforcement learning is discussed in the context of robotic-assisted surgery, and generalized deep-learning methods for genomics are reviewed.

PMID:
30617335
DOI:
10.1038/s41591-018-0316-z
[Indexed for MEDLINE]

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