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我们是否应该依靠人工智能来帮助避免在重大手术患者选择中的偏见?

Should We Rely on AI to Help Avoid Bias in Patient Selection for Major Surgery?

机构信息

Director of bioethics for the central region at Hackensack Meridian Health and clinical assistant professor of surgery at Hackensack Meridian School of Medicine in Nutley, New Jersey.

Legal education specialist.

出版信息

AMA J Ethics. 2022 Aug 1;24(8):E773-780. doi: 10.1001/amajethics.2022.773.

DOI:10.1001/amajethics.2022.773
PMID:35976935
Abstract

Many regard iatrogenic injuries as consequences of diagnosis or intervention actions. But inaction-not offering indicated major surgery-can also result in iatrogenic injury. This article explores some surgeons' overestimations of operative risk based on patients' race and socioeconomic status as unduly influential in their decisions about whether to perform major cancer or cardiac surgery on some patients with appropriate clinical indications. This article also considers artificial intelligence and machine learning-based clinical decision support systems that might offer more accurate, individualized risk assessment that could make patient selection processes more equitable, thereby mitigating racial and ethnic inequity in cancer and cardiac disease.

摘要

许多人认为医源性损伤是诊断或干预措施的结果。但是,不作为——不提供有指征的大手术——也可能导致医源性损伤。本文探讨了一些外科医生根据患者的种族和社会经济地位过高估计手术风险,从而对某些具有适当临床指征的患者是否进行大癌症或心脏手术的决策产生了不当影响。本文还考虑了基于人工智能和机器学习的临床决策支持系统,这些系统可能提供更准确、个体化的风险评估,从而使患者选择过程更加公平,从而减轻癌症和心脏病中的种族和民族不平等。

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