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手术中的人工智能:对使用和验证的系统审查

Nitzan Kenig¹, Javier Monton Echeverria², Aina Muntaner Vives³

¹Department of Plastic Surgery, Quironsalud Palmaplanas Hospital, 07010 Palma, Spain.

Journal of clinical medicine

|December 17, 2024

概括

手术中的人工智能 (AI) 是有前途的,但缺乏标准化的验证. 一个新的外科验证分数 (SURVAS) 旨在确保人工智能模型的安全性和准确性,以获得更好的患者结果.

科学领域:

医疗信息学医疗信息学
手术技术手术技术
医疗保健中的人工智能

背景情况:

人工智能 (AI) 在外科环境中越来越多地使用,但缺乏标准化的验证协议.
确保人工智能模型的准确性和患者安全性在广泛临床采用之前至关重要.
低于最佳的验证风险是整合未经证实的AI,可能会对患者的治疗结果产生负面影响.

研究的目的:

审查当前的AI模型验证和在临床外科手术中的使用.
为人工智能模型在手术中的验证提出一个新的分类系统.

主要方法:

对PubMed和Cochrane数据库进行系统审查.
关键词:"验证"",人工智能"",外科手术".
在研究选择和数据提取方面遵循PRISMA指南.

主要成果:

从7627篇最初的文章中,包括了102项研究 (2,837,211名患者).
开发了手术验证分数 (SURVAS) 分类系统.
只有45%的研究使用了高证据验证方法;14%提供了公共数据集. 人工智能主要用于术前风险评估.

结论:

人工智能具有重要的外科应用,主要用于术前风险评估和决策.
目前的人工智能验证质量低于最佳,公共数据的可用性有限.
像SURVAS这样的分类系统可以帮助临床医生在临床使用之前评估AI模型的有效性.

关键词:

人工智能的人工智能是人工智能.人机交互的人机交互机器学习是机器学习.手术手术手术手术手术手术手术验证验证的时间

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