患者对基于人工智能的手术决策支持的观点
Sara Ben Hmido1,2, Houssam Abder Rahim3, Corrette Ploem4
1Department of Surgery, Amsterdam UMC Locatie VUmc, Amsterdam, Noord-Holland, The Netherlands.
BMJ surgery, interventions, & health technologies
|April 4, 2025
概括
患者通常在结直肠外科手术 (CRS) 中接受手术内预测机器学习 (IPML). 他们将IPML视为一个咨询工具,强调外科医生.
科学领域:
- 医疗保健技术 医疗保健技术 医疗保健技术
- 手术方面的创新.
- 患者的观点 患者的观点
背景情况:
- 预测性机器学习 (ML) 在医疗保健领域正在迅速发展,特别是在手术决策方面.
- 关于患者在整个临床过程中使用ML的观点的研究有限.
- 这项研究探讨了在结直肠外科手术 (CRS) 中对手术内预测机器学习 (IPML) 的患者观点,特别是用于预测结直肠静脉泄漏 (CAL).
研究的目的:
- 调查患者对在CRS中实施IPML模型的看法.
- 了解患者对IPML在决策和临床信息传递中的作用的看法.
主要方法:
- 使用焦点小组和半结构面试进行定性研究设计.
- 描述性主题分析以确定患者的主题和态度.
- 通过和分析确定样本大小 (n=19名患者).
主要成果:
- 患者通常在CRS中积极感知IPML模型.
- 参与者将IPML视为咨询工具,外科医生保留主要决策权.
- 强调个性化沟通,生活质量和外科医生覆盖能力.
结论:
- 当外科医生保持覆盖权威和透明文档时,CRS中的IPML得到了很好的接待.
- 患者对外科医生的信任对于IPML的接受至关重要,需要明确的沟通.
- 量身定制的沟通和解决对生活质量的影响 (解肠切除与静脉切除) 是至关重要的.
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