通过自动化与基于规则的人工智能优化CAPD患者监测:系统性比较审查
Satriyo Dwi Suryantoro1, Chastine Fatichah2, Dini Adni Navastara2
1Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
International journal of nephrology and renovascular disease
|December 22, 2025
概括
人工智能 (AI) 增强了持续的门诊腹腔透析 (CAPD) 监测. 自动化人工智能提供了精确性,而基于规则的系统适合低资源的设置,建议一种混合模式,以获得最佳的CAPD护理.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 连续门诊腹腔透析 (CAPD) 是一种重要的置换疗法,特别是在发展中国家.
- 由于CAPD面临着腹膜炎和液体过载等挑战,因此需要改善监测和决策支持.
- 人工智能 (AI) 提出了增强CAPD管理的潜在解决方案.
研究的目的:
- 系统地审查和比较基于规则的AI系统和CAPD监控的自动机器学习方法.
- 评估AI在临床结果,患者坚持,操作效率,成本和可用性方面的有效性.
- 探索自动化AI用于CAPD中的透析图像分类.
主要方法:
- 2020年1月1日至2025年5月20日期间发表的文献的系统审查.
- 包括PubMed,Scopus,Google Scholar和IEE Xplore的研究,其中有24项研究进行了合成.
- 评估14项符合资格的研究,重点关注用于CAPD监测和管理的AI实施.
主要成果:
- 自动化的人工智能系统表现出卓越的精度和早期检测能力.
- 基于规则的AI模型在资源有限的医疗环境中提供了实际优势.
- 人工智能,包括用于透析图像分类的机器学习,在CAPD管理中显示出前景.
结论:
- 为CAPD监测提出了混合人工智能集成模型,该模型结合了基于规则的和自动化的方法.
- 这种混合模型旨在最大限度地提高临床准确性,成本效益和可访问性.
- 根据国家指导方针和保险计划定制AI解决方案对于成功实施至关重要.
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