深度学习和心电图:对心血管疾病诊断和管理当前技术的系统审查
1Cardiovascular Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Biomedical engineering online
|February 23, 2025
概括
深度学习与心电图 (ECG) 结合,在诊断心血管疾病方面取得了重大进展. 本综述指导了对人工智能驱动的心脏诊断的进一步研究.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 生物医学工程 生物医学工程
背景情况:
- 心血管疾病 (CVD) 仍然是全球主要的死亡原因.
- 电心电图 (ECG) 是心脏评估的一个基本工具.
- 集成先进的计算方法,如深度学习,提供了新的诊断潜力.
研究的目的:
- 系统地审查最近深度学习应用在心血管疾病中ECG分析的进展.
- 提供当前研究格局的全面概述.
- 确定趋势并指导未来的研究方向.
主要方法:
- 进行了系统的文献搜索,确定了198个高质量的出版物.
- 出版物被细致地分类和分层分类.
- 审查的重点是深度学习,心电图和心血管疾病的交集.
主要成果:
- 深度学习模型在从心电图数据中检测各种心血管疾病方面表现出越来越高的有效性.
- 在不同类型的心血管疾病中观察到显著的进展.
- 该领域正在迅速发展,许多创新的方法正在出现.
结论:
- 深度学习与心电图相结合,代表了心血管疾病诊断和管理的强大范式.
- 经过审查的文献强调了人工智能在心脏病学中的变革潜力.
- 鼓励进一步的研究将这些进展转化为临床实践.
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