Artificial Intelligence: Predicting Perioperative Problems

被引:0
作者
Harris, Joseph [1 ]
Matthews, James [1 ]
机构
[1] Royal London Hosp, Dept Anaesthesia, London, England
关键词
anaesthesia; perioperative medicine; artificial intelligence; machine learning; data science; risk prediction;
D O I
10.12968/hmed.2024.0262
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The rapidly developing field of artificial intelligence (AI) may soon equip clinicians with algorithms that model and predict perioperative problems with extreme accuracy. Here, we outline emerging AI applications in preoperative risk stratification and intraoperative event prediction, where algorithm performance has been shown to outstrip commonly used conventional risk prediction tools. While offering an enticing view of a novel perioperative practice with superhuman foresight, AI's limited scope and lack of transparency remain key challenges for widespread adoption. As yet it is unclear whether machine learning alone can influence human clinical practice to exert real-world effects on patient outcomes.
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收藏
页数:4
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