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对用于评估基于人工智能的医疗设备用于心力衰竭的方法进行范围的元综述

Rossella Di Bidino¹, Davide Piaggio², Martina Andellini²

¹Fondazione Policlinico Universitario Agostino Gemelli IRCCS-The Graduate School of Health Economics and Management (ALTEMS), 00168 Rome, Italy.

Bioengineering (Basel, Switzerland)

|October 28, 2023

概括

医疗技术评估 (HTA) 需要在医疗设备中使用人工智能和机器学习 (AI/ML) 的常用方法. 这篇评论强调了AI/ML用于心力衰竭管理,确定深度学习和电子健康记录是关键.

科学领域:

医疗技术医疗技术医学技术
医疗信息学医疗信息学
生物医学工程生物医学工程

背景情况:

人工智能和机器学习 (AI/ML) 越来越多地被整合到医疗器械中.
目前的卫生技术评估 (HTA) 方法在解决基于AI/ML的医疗药物方面落后.
在医疗保健中,对AI/ML进行标准化的HTA方法至关重要.

研究的目的:

对评估基于AI/ML的MD的方法进行范围的元综述.
专注于AI/ML在心力衰竭 (HF) 管理中的应用.
确定AI/ML的HTA中存在的差距和需要改进的领域.

主要方法:

从1974年1月到2022年10月进行了全面的文献搜索.
使用了一个覆盖范围的meta-review方法.
在查后,包括了21个相关的评论,主要来自北美和欧洲.

主要成果:

深度学习成为最常用的AI/ML方法.
电子健康记录和注册表是AI/ML算法的主要数据来源.
大多数审查 (19/21) 专注于HF风险预测和早期诊断;许多报告对HF发病率/进展和停留时间的影响.

结论:

需要对基于AI/ML的医学博士的HTA进行重大改进.
提高关键领域包括AI/ML研究和数据源的质量评估.
定义明确的标准来选择适当的AI/ML算法对于有效的HTA至关重要.

关键词:

人工智能的人工智能是人工智能.决策是做出决策的过程.卫生技术评估卫生技术评估心脏衰竭是因为心脏衰竭.机器学习是机器学习.范围审查范围审查审查价值评估评估的价值评估是如何进行的

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