预测性医疗保健中的人工智能:系统性审查
Abeer Al-Nafjan1, Amaal Aljuhani1, Arwa Alshebel1
1Computer Science Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia.
Journal of clinical medicine
|October 16, 2025
概括
人工智能 (AI) 和机器学习 (ML) 正在彻底改变医疗预测分析,以改善患者护理. 未来的研究必须优先考虑可解释的,保护隐私的AI模型和标准化的评估.
科学领域:
- 医疗保健人工智能的人工智能
- 机器学习在医学中的应用
- 预测分析是一种预测分析.
背景情况:
- 人工智能和机器学习显著增强了医疗保健预测分析.
- 数据驱动的方法和人工智能集成在临床环境中越来越受欢迎.
- 越来越多的出版物强调了医疗保健中的创新AI应用.
研究的目的:
- 综合最近关于AI/ML在疾病预测中的应用的证据.
- 识别常见的AI/ML模型,评估指标和挑战.
- 提供关于人工智能在医疗保健中的当前状态和未来方向的见解.
主要方法:
- 从2021-2025年开始的系统文献综述.
- 在 Web of Science 和 Google Scholar 进行的搜索.
- 包括专注于AI/ML技术用于疾病预测的研究.
主要成果:
- 22项研究符合纳入标准.
- 基于树的集合 (随机森林,XGBoost) 和深度学习 (CNN,LSTM) 是普遍存在的.
- AUROC,F1分数,准确度和灵敏度是常见的评估指标.
- 主要挑战包括数据隐私,工作流集成,可解释性和数据质量.
结论:
- 未来的研究应该专注于可解释的AI模型,以获得临床信任.
- 强大的隐私保护技术对于保护患者数据至关重要.
- 需要标准化的评估框架来有效评估模型性能.
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