Is Artificial Intelligence Better Than Human Clinicians in Predicting Patient Outcomes?

被引:18
|
作者
Lee, Joon [1 ,2 ,3 ]
机构
[1] Univ Calgary, Cumming Sch Med, Data Intelligence Hlth Lab, 3280 Hosp Dr NW,TRW 5E17, Calgary, AB T2N 4Z6, Canada
[2] Univ Calgary, Cumming Sch Med, Dept Community Hlth Sci, Calgary, AB, Canada
[3] Univ Calgary, Cumming Sch Med, Dept Cardiac Sci, Calgary, AB, Canada
关键词
patient outcome prediction; artificial intelligence; machine learning; human-generated predictions; human-AI symbiosis; DECISION-MAKING; MACHINE; CARE; CLASSIFICATION; PERFORMANCE; MEDICINE; SURVIVAL; CANCER; RISK;
D O I
10.2196/19918
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
In contrast with medical imaging diagnostics powered by artificial intelligence (AI), in which deep learning has led to breakthroughs in recent years, patient outcome prediction poses an inherently challenging problem because it focuses on events that have not yet occurred. Interestingly, the performance of machine learning-based patient outcome prediction models has rarely been compared with that of human clinicians in the literature. Human intuition and insight may be sources of underused predictive information that AI will not be able to identify in electronic data. Both human and AI predictions should be investigated together with the aim of achieving a human-AI symbiosis that synergistically and complementarily combines AI with the predictive abilities of clinicians.
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页数:5
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