CarDS-Plus ECG 平台:为便携式和可穿戴设备心电图表开发多平台人工智能工具包的开发和可行性评估
Sumukh Vasisht Shankar1,2, Evangelos K Oikonomou1,2, Rohan Khera1,2,3,4
1Cardiovascular Data Science (CarDS) Lab, Yale School of Medicine, New Haven, CT.
medRxiv : the preprint server for health sciences
|October 24, 2023
概括
这项研究开发了一个多平台系统,用于基于人工智能的快速解释可穿戴设备的单导电心电图 (ECG). 该平台高效地处理ECG数据,以加快临床诊断和心血管健康监测.
科学领域:
- 生物医学工程 生物医学工程
- 心血管技术的心血管技术
- 医疗保健中的人工智能
背景情况:
- 像Apple Watch和KardiaMobile这样的可穿戴设备可以持续监控个人健康.
- 这些设备的单导电心电图 (ECG) 对心血管健康评估至关重要.
- 人工智能 (AI) 在解释ECG数据以进行临床诊断方面表现有前途.
结论:
- 开发的平台可以实现基于AI的高效,多平台的ECG解释.
- 获取到报告的平均时间不到66秒,表明快速部署.
- 这一策略对于将可穿戴心电图中的AI发现转化为临床影响至关重要.
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