开发一个基于人工智能的自动分析儿科Apple WatchiECGs的开发
L Teich1, D Franke2, A Michaelis1
1Department for Pediatric Cardiology, University of Leipzig - Heart Center, Leipzig, Germany.
Frontiers in pediatrics
|June 26, 2023
概括
开发了一种人工智能 (AI) 算法,可以自动解释来自Apple Watch的儿科心电图 (iECG). 这种人工智能有望改善儿科iECG分析,尽管对于复杂的病例需要进一步培训.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 儿科健康 儿科健康
背景情况:
- 果手表可以记录儿童的基于事件的心电图 (iECG).
- 对于儿科iECGs,Apple Watch软件的自动心律分类是不准确的.
- 目前儿童的iECG分析需要由儿科心脏病专家进行解释.
研究的目的:
- 开发一种基于人工智能 (AI) 的算法,用于自动解释儿科Apple WatchiECGs.
- 提高儿科iECG分析的准确性和效率.
主要方法:
- 一个人工智能算法被设计和训练使用预先记录,手动分类iECGs.
- 该算法在莱比锡心脏中心的48名儿科患者的前队列上进行了评估.
- 人工智能iECG评价与儿童心脏病学家对12导电图解释的黄金标准进行了比较.
主要成果:
- 人工智能算法实现了96.7%的特异性和66.7%的敏感性来分类正常的鼻节律.
- 本研究介绍了第一个人工智能算法,用于自动对儿科iECGs进行心律分类.
结论:
- 开发的AI算法为基于AI的儿科iECG分析的未来进步提供了基础.
- 用更多数据进行进一步的AI培训对于建立基于AI的iECG分析作为复杂儿科患者的临床工具至关重要.
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