Machine Learning and Precision Medicine in Emergency Medicine: The Basics

被引:2
|
作者
Lee, Sangil [1 ]
Lam, Samuel H. [2 ]
Rocha, Thiago Augusto Hernandes [3 ]
Fleischman, Ross J. [4 ]
Staton, Catherine A. [3 ]
Taylor, Richard [5 ]
Limkakeng, Alexander T. [3 ]
机构
[1] Univ Iowa, Coll Med, Emergency Med, Iowa City, IA 52242 USA
[2] Sutter Med Ctr, Emergency Med, Sacramento, CA USA
[3] Duke Univ, Div Emergency Med, Dept Surg, Sch Med, Durham, NC 27706 USA
[4] Harbor UCLA Med Ctr, Emergency Med, Los Angeles, CA USA
[5] Yale Univ, Dept Emergency Med, New Haven, CT USA
关键词
machine learning; artificial intelligence; precision medicine; research in emergency medicine; risk prediction; ARTIFICIAL-INTELLIGENCE; CHEST-PAIN; HEART SCORE; PREDICTION; TRIAGE; RISK;
D O I
10.7759/cureus.17636
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
As machine learning (ML) and precision medicine become more readily available and used in practice, emergency physicians must understand the potential advantages and limitations of the technology. This narrative review focuses on the key components of machine learning, artificial intelligence, and precision medicine in emergency medicine (EM). Based on the content expertise, we identified articles from EM literature. The authors provided a narrative summary of each piece of literature. Next, the authors provided an introduction of the concepts of ML, artificial intelligence as an extension of ML, and precision medicine. This was followed by concrete examples of their applications in practice and research. Subsequently, we shared our thoughts on how to consume the existing research in these subjects and conduct high-quality research for academic emergency medicine. We foresee that the EM community will continue to adapt machine learning, artificial intelligence, and precision medicine in research and practice. We described several key components using our expertise.
引用
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页数:10
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