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

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ID: 117527
2020
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Abstract
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. [J Med Internet Res 2020;22(8):e19918]
Reference Key
lee2020journalis Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Joon Lee;
Journal Journal of medical Internet research
Year 2020
DOI
doi:10.2196/19918
URL
https://www.jmir.org/2020/8/e19918
Keywords
medical Internet research medicine journal ehealth JMIR open access publishing medical research medical informaticspatient outcome prediction;artificial intelligence;machine learning;human-generated predictions;human-ai symbiosis

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