Abstract
Life sciences researchers using artificial intelligence (AI) are under pressure to innovate faster than ever. Large, multilevel, and integrated data sets offer the promise of unlocking novel insights and accelerating breakthroughs. Although more data are available than ever, only a fraction is being curated, integrated, understood, and analyzed. AI focuses on how computers learn from data and mimic human thought processes. AI increases learning capacity and provides decision support system at scales that are transforming the future of health care. This article is a review of applications for machine learning in health care with a focus on clinical, translational, and public health applications with an overview of the important role of privacy, data sharing, and genetic information.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 795-801 |
| Number of pages | 7 |
| Journal | American Journal of Medicine |
| Volume | 132 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Medicine
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