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人工智能在高伤心肌病中:个性化风险预测和管理的进步,挑战和未来方向
Moiud Mohyeldin1,2,3, Feras O Mohamed4, Marcos Molina1
1Internal Medicine, BronxCare Health System, Bronx, USA.
Cureus
|August 14, 2025
概括
人工智能 (AI) 显著改善了超性心肌病 (HCM) 风险预测和管理. 人工智能工具在识别心律失常,预测突发心脏病死亡以及个性化基因测试和治疗策略方面表现出高准确性.
科学领域:
- 心血管医学 心血管医学
- 生物医学工程 生物医学工程
- 医疗信息学 医疗信息学
背景情况:
- 增高性心肌病变 (HCM) 是一种遗传性心脏病,目前对心脏突然死亡的风险分层不足.
- 预测HCM患者临床结果的现有方法的准确性有限.
- 需要先进的工具来个性化HCM的风险预测和管理.
研究的目的:
- 审查人工智能 (AI) 在转换个性化HCM风险预测方面的验证的临床应用.
- 检查人工智能是如何增强的管理和治疗策略,对多变性心肌病.
- 为了确定当前的挑战和未来的方向,在HCM护理中实施AI.
主要方法:
- 在PubMed,IEEE Xplore,Web of Science和Scopus (2015年1月至2025年1月) 的综合文献搜索.
- 包含对HCM人工智能应用的同行评审研究,并使用验证的绩效指标.
- 分析人工智能技术,临床应用,性能和实施障碍.
主要成果:
- 机器学习模型在预测心室节律失常方面显示出高准确度 (83%),识别了新的预测因子.
- 对心电图的深度学习分析在预测突发心脏病死亡方面达到85-87%的准确性,超过了传统的得分.
- 人工智能增强了基因测试 (96%准确率) 和心脏MRI分析,实时查和治疗决策支持工具显示>90%的准确性.
结论:
- 人工智能为改善高性心肌病的风险预测和管理提供了变革性的潜力.
- 在心电图,遗传学和成像学中验证的AI应用正在推进个性化HCM护理.
- 解决数据偏差,标准化,监管和可解释性挑战对于广泛的临床整合至关重要.
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