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慢性病管理中的人工智能:一个范围审查
Charumathi Sabanayagam1,2,3, Riswana Banu1, Cynthia Lim4
1Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
Theranostics
|April 14, 2025
概括
人工智能 (AI) 在通过早期检测和个性化治疗来改善慢性病 (CKD) 管理方面非常有前途. 解决数据,准确性和整合方面的挑战是实现AI的关键.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 慢性病 (CKD) 是全球健康面临的重大挑战,需要先进的管理策略.
- 现有的方法需要创新,以减轻慢性瘤的负担,包括相关的心血管疾病,功能衰竭和死亡风险.
研究的目的:
- 进行范围审查,确定人工智能 (AI) 应用程序,以加强CKD管理.
- 检查挑战,并提出解决方案,在CKD护理中整合AI.
主要方法:
- 对41篇文章 (2014-2024) 的系统审查,重点关注机器学习 (ML),深度学习 (DL),自然语言处理 (NLP) 和大语言模型 (LLM) 等人工智能技术.
- 分析集中在四个关键领域:早期检测,风险分层,治疗建议和患者沟通.
主要成果:
- 确定的AI应用包括早期检测的DL (6项研究),风险分层/预测的ML (14项研究) 和治疗建议 (4项研究),以及患者护理的NLP/LLM (17项研究).
- 主要挑战涉及数据质量,模型准确性,可解释性,工作流集成,用户培训和监管障碍.
结论:
- 人工智能具有显著的潜力,可以改善慢性病管理中的早期检测,预测和患者结果.
- 为了在临床实践中开发安全,合规和有效的AI集成协议,多学科的合作是必不可少的.
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