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体育医学中的人工智能:为运动员安全重塑心电图分析 - - 一篇叙述性评论
Alina Maria Smaranda1,2, Teodora Simina Drăgoiu2, Adela Caramoci1,3
1Discipline of Sports Medicine, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania.
Sports (Basel, Switzerland)
|June 26, 2024
概括
人工智能 (AI) 增强了运动员参加前考试中的心电图 (ECG) 分析. 人工智能提高了严重心脏病的检测,促进了更安全的体育参与.
科学领域:
- 运动医学 运动医学
- 心脏病学 心脏病学
- 生物医学工程 生物医学工程
背景情况:
- 心血管风险,包括心脏突然死亡,是运动员的一个担忧.
- 传统的心电图 (ECG) 分析在区分良性适应和严重情况方面存在局限性.
- 人工智能 (AI) 具有提高体育医学中ECG解释的潜力.
研究的目的:
- 审查机器学习 (ML) 和深度学习 (DL) 在AI增强的运动员心电图分析中的应用.
- 探索AI在改善参与前检查 (PPE) 期间检测心脏异常方面的作用.
- 支持体育医学专业人员将AI整合到运动员心血管查中.
主要方法:
- 一篇关于过去十年出版的文学作品的叙事评论.
- 使用PubMed和谷歌学者数据库进行的文献搜索.
- 专注于应用AI,ML和DL在体育医学和运动员查的背景下对ECG解释的研究.
主要成果:
- 人工智能算法在识别复杂的心脏模式方面表现得精确,传统方法经常错过.
- 人工智能在体育医学中的日益普及凸显了它对心血管健康的预测能力.
- 将人工智能集成到可穿戴技术中,有助于持续监控运动员.
结论:
- 人工智能驱动的心电图分析显著提高了运动员护理的诊断准确性和效率.
- 人工智能有助于早期检测和更有效地监测接受PPE运动员的心血管疾病.
- 将传统查与人工智能技术结合起来,对于推进运动员心血管健康管理至关重要.
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