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使用人工智能检测运动员心律障碍:一个范围审查
Amie Kapusniak1, Natalia Medrano Lara2, Peta L Hitchens2
1School of Animal and Veterinary Science, University of Adelaide, Roseworthy, SA, Australia.
Journal of veterinary internal medicine
|September 29, 2025
概括
人工智能 (AI) 显示出改善马匹心电图 (ECG) 分析的前景,有助于检测心律失常. 需要进一步开发特定于马类生理学的AI算法,以实时监测运动动物的心脏.
科学领域:
- 兽医心脏病学 兽医心脏病学
- 生物医学工程 生物医学工程
- 人工智能在医学中的应用
背景情况:
- 与运动相关的心律失常在马匹运动员中很普遍,增加了突然心脏病死亡的风险.
- 目前马的心电图 (ECG) 解释是主观的,耗时的,轻微的节律障碍的临床意义不明确.
- 人工智能 (AI) 正在成为一种工具,以增强人类医学中的ECG解释.
研究的目的:
- 评估AI在ECG中检测心律失常的应用.
- 评估人工智能在运动物种中的当前和潜在使用情况,重点是马.
- 审查人工智能在解释心电图以检测心律失常方面的作用.
主要方法:
- 对17项同行评审研究 (2000-2024) 进行了范围审查.
- 研究包括人类 (13),马 (3),狗 (1) 的心电图数据.
- 评估了人工智能模型,诊断准确性和对行使心电图的相关性.
主要成果:
- 深度学习模型在人类心电图解释方面取得了高准确度 (79.4%-98.6%).
- 在使用归还分析和转移学习的马身上观察到有希望的结果.
- 限制包括兽医研究中的小样本大小和特定物种的ECG形态学.
结论:
- 人工智能有可能在马匹运动员的心电图上准确有效地检测出心律失常.
- 特定物种的人工智能算法可以在运动期间实现实时心脏监测.
- 人工智能可以支持运动马的增强心血管评估.
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