深度学习
计算机科学
人工智能
背景(考古学)
强化学习
钥匙(锁)
医疗保健
数据科学
人机交互
计算机安全
经济增长
生物
古生物学
经济
作者
Andre Esteva,Alexandre Robicquet,Bharath Ramsundar,Volodymyr Kuleshov,Mark A. DePristo,Katherine Chou,Claire Cui,Greg S. Corrado,Sebastian Thrun,Jeff Dean
出处
期刊:Nature Medicine
[Springer Nature]
日期:2018-12-24
卷期号:25 (1): 24-29
被引量:2520
标识
DOI:10.1038/s41591-018-0316-z
摘要
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.
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