机器学习和人工智能在心律失常和电生理学中的作用
Muhammad Umer Riaz Gondal1, Hassan Atta Mehdi2, Raja Ram Khenhrani3
1From the Department of Medicine, Reading Hospital, PA.
Cardiology in review
|May 18, 2024
概括
机器学习 (ML) 彻底改变了心血管医学,特别是在心脏电生理学和心律失常方面. 这次审查探讨了ML的ML.
科学领域:
- 心血管医学和心脏电生理学.
- 人工智能和机器学习应用程序
背景情况:
- 机器学习 (ML),人工智能 (AI) 的一个子集,使系统能够从数据中学习,推动跨部门的创新.
- 心血管医学越来越多地采用ML,重点关注心脏电生理学和心律失常研究.
- 虽然电心电图解读中的ML已经得到了很好的研究,但它在心律失常机制,映射和管理方面的更广泛作用尚未得到充分探索.
研究的目的:
- 在心脏电生理学和心律失常方面提供各种机器学习应用的全面审查.
- 为研究心律失常的研究人员提供ML原则的基础知识.
- 展示ML在基础科学,实验/计算研究,心脏映射和转移性心律失常管理方面的潜力.
主要方法:
- 在心脏电生理学和心律失常中对机器学习应用的文献综述.
- 内容组织成三个部分:机器学习原则,机器学习在电生理学研究中的应用,以及挑战/未来前景.
- 深入分析利用ML方法论在心律失常研究中的研究,突出突出进展.
主要成果:
- 确定了自动ECG解释之外的各种ML应用,包括基础科学,实验/计算研究和绘图技术.
- 证明了ML方法在理解和管理心律失常方面的广泛潜力.
- 概述了ML在心脏电生理学研究中的关键挑战和未来方向.
结论:
- 机器学习为推进心脏电生理学和心律失常研究提供了显著的,多方面的潜力.
- 进一步探索和整合ML对于应对当前挑战和释放该领域未来的突破至关重要.
- 本综述作为一个基础资源和路线图,用于ML驱动的创新在心律失常科学.
相关概念视频
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