用人工智能启用心电图的临床实施,用于检测多变性心肌病变
Christopher J Love1, Joshua Lampert2, David Huneycutt3
1Viz Ai Inc, San Francisco, California, USA cjlove.mit@gmail.com.
Heart (British Cardiac Society)
|April 16, 2025
概括
一个人工智能 (AI) 工具通过心电图成功地通过心电图识别了疑似多变性心肌病 (HCM) 病例,从而导致了新的诊断. 这种AI-ECG方法在改善临床实践中的HCM检测方面表现有前途.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
背景情况:
- 缩性心肌病变 (HCM) 经常被诊断不足.
- 人工智能 (AI) 提供了一种潜在的解决方案,用于使用心电图早期检测HCM.
- 人工智能对怀疑HCM的临床实施尚未先前研究.
研究的目的:
- 评估AI-ECG软件的临床实施,用于识别疑似HCM的患者.
- 评估AI在提醒临床医生潜在的HCM病例方面的有效性.
主要方法:
- 进行了一项前性,开放的,多中心的队列研究.
- 一个AI-ECG软件Viz HCM从2023年1月到12月在五个医疗保健系统中实施.
- 该研究侧重于18岁以上没有先前HCM诊断的患者,分析警报观看率和后续行动.
主要成果:
- 在145,848个查的心电图中,3% (4,348) 触发了怀疑HCM的警报.
- 用户查看了69%的警报病例,并招募了217名患者进行随访.
- 在被招募的患者中,共有17例新的HCM诊断 (7.8%) 得到证实.
结论:
- 基于人工智能的心电图分析可以成功地集成到临床工作流程中,用于识别新的HCM患者.
- 需要进一步的研究来评估可扩展性,并将这种AI方法与标准护理进行比较.
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