使用人工智能从患者报告的结果指标来预测患者的结果:一个范围审查
Zuzanna Wójcik1, Vania Dimitrova2, Lorraine Warrington3
1UKRI Centre for Doctoral Training in Artificial Intelligence for Medical Diagnosis and Care, University of Leeds, Leeds, UK. sczw@leeds.ac.uk.
Health and quality of life outcomes
|April 11, 2025
概括
人工智能 (AI) 和患者报告的结果测量 (PROM) 显示出预测患者结果的前景. 然而,不一致的报告和缺乏外部验证阻碍了使用PROM数据的AI模型的临床应用.
科学领域:
- 研究人工智能 (AI) 和患者报告的结果测量 (PROM) 的交叉点.
- 专注于人工智能的应用,使用PROM数据预测患者的结果.
背景情况:
- 人工智能模型已经成功地使用临床数据预测了患者的结果.
- 缺乏用于使用人工智能与PROMs的系统指导,导致模型开发和临床翻译中的不一致性.
研究的目的:
- 识别和总结用于PROMs预测患者结果的AI方法.
- 突出不一致性,并为涉及PROM的AI研究提供建议.
主要方法:
- 在多个主要科学数据库中进行了范围审查.
- 包括的研究使用PROM数据作为预测患者结果的AI模型的输入变量.
主要成果:
- 包括94项研究,AI和PROM最常用于骨科和瘤学.
- 识别了超参数报告不良,数据处理不一致 (不平衡,缺失),常见的缺失是外部验证,种族数据和利益相关方参与.
结论:
- 人工智能研究与PROM的不一致性降低了研究的可重现性.
- 建议强调外部验证和利益相关者的参与,以改善人工智能模型的临床应用.
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