医学问卷中的人工智能:范围审查
Xuexing Luo1, Yiyuan Li1, Jing Xu1
1Faculty of Humanities and Arts, Macau University of Science and Technology, Macau, China.
Journal of medical Internet research
|June 23, 2025
概括
人工智能 (AI) 在提高医疗问卷以进行评估,开发和预测方面表现有前途,尽管目前的研究局限性. 未来的工作必须解决临床整合的解释性,验证和伦理问题.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 心理测量评估 心理测量评估
背景情况:
- 全球心理健康负担很大,目前诊断问卷的局限性导致了不准确的诊断.
- COVID-19 流行病增加了医疗保健方面的挑战,突出了对先进诊断工具的需求.
- 人工智能 (AI) 为改善医疗保健中的诊断准确性和临床决策提供了潜在的解决方案.
研究的目的:
- 在医学问卷中系统地审查人工智能的应用,好处和挑战.
- 专注于AI在医学问卷中的评估,开发和预测功能中的作用.
- 评估AI在解决传统诊断工具局限性的价值.
主要方法:
- 从创建到2024年9月,对5个数据库 (PubMed,Embase,Cochrane图书馆,Web of Science,CNKI) 的系统审查.
- 纳入标准侧重于同行评审的研究,将AI应用于具有可衡量的结果的医疗,心理或生理问卷.
- 数据提取,使用乔安娜·布里格斯研究所工具进行质量评估和叙事综合,由三个独立审稿人进行.
主要成果:
- 14项研究符合纳入标准,确定了24种应用到问卷中的AI技术 (例如随机森林,ChatGPT).
- 人工智能在评估方面表现出优势 (例如,区分条件的准确性为92.18%),发展 (例如,ChatGPT用于文化能力的尺度) 和预测 (白内障手术风险AUC为0.790).
- 大多数研究 (79%) 仍处于探索阶段,其方法质量和局限性适度,例如缺乏对照组和不充分的验证.
结论:
- 在医疗问卷中集成AI应用具有显著的潜力,可以提高诊断效率,加快规模开发,并促进早期干预.
- 进一步的研究对于提高模型解释性,系统兼容性,验证标准化和道德治理至关重要.
- 解决数据隐私,临床整合和透明度等挑战对于在医学问卷中有效实施AI至关重要.
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