"黑子"人工智能用于死亡率预测:对息护理团队,患者和护理人员的观点进行混合方法研究
Beatrice Bridge1, Ahmed Y Alasmar2, Lauren Gunn-Sandell3
1School of Medicine, University of Colorado Anschutz, Aurora, CO, USA.
Annals of palliative medicine
|March 11, 2026
概括
可解释的人工智能 (AI) 在息治疗中至关重要. 虽然准确性可能会降低对可解释性的需求,但患者与临床医生的沟通强调了它对AI死亡率预测工具的重要性.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 息护理研究 息护理研究
背景情况:
- 基于人工智能 (AI) 的死亡率预测算法为患者的预后意识和以人为中心的息护理提供了潜在的好处.
- 人工智能输出的可解释性是影响患者和医疗团队采用它们的关键因素.
研究的目的:
- 调查息护理利益相关者对人工智能算法的解释性方面的观点.
- 了解影响AI可解释性在息护理环境中的担忧或缺乏担忧的因素.
主要方法:
- 一个连续的混合方法研究,涉及80名息护理临床医生,患者和护理人员的采访.
- 对53次专注于人工智能可解释性的访谈进行主题分析.
- 一项对2500名息护理医生的调查,其中537个完整的反应被描述性和多变量分析.
主要成果:
- 在受访者中,对人工智能可解释性的看法从仅仅关注到仅仅不关注,同时也存在不同的观点.
- 关注的原因包括数据透明度,不信任,沟通问题,偏见和准确性;不关注的原因是AI的非独特性,准确性,整合性和基于证据的性质.
- 75%的医生表示对无法解释的AI有中度到强烈的担忧;感知不准确性和男性性别与更高的担忧有关.
结论:
- 人工智能死亡率预测模型的感知精度可能会降低对可解释性的需求.
- 由于强调沟通,可解释性仍然是息护理的核心.
- 未来的人工智能开发应该优先考虑准确性和可解释性,以便在护理地点应用.
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