人工智能心电图协助诊断晕厥原因探索
Exploration of Artificial Intelligence Electrocardiogram to Assist in Diagnosing the Causes of Syncope
刘彤 1高欣怡 1李歆慕1
作者信息
- 1. 300211 天津市,天津市心血管病离子与分子机能重点实验室天津医科大学第二医院心脏科天津心脏病学研究所
- 折叠
摘要
心电图记录和分析心动周期的电活动变化,对识别晕厥的潜在病因具有重要提示作用.人工智能赋能的心电图(AI-ECG)在晕厥的病因诊断和风险预测等方面展现出不容忽视的巨大潜力.基于AI-ECG表型的临床决策评分已被开发用于晕厥的病因诊断,AI-ECG对晕厥风险分层和临床管理的影响正在不断显现.
Abstract
Electrocardiogram(ECG)recording and analysis of the changes of electrical activity in the cardiac cycle is of great significance for identifying the potential causes of syncope.Artificial intelligence-enabled electrocardiogram(AI-ECG)has shown great potential in diagnosing the etiology and predicting the risk of syncope.Clinical decision scores based on the AI-ECG phenotype have been developed to assist in the etiological diagnosis of syncope,and the impact of AI-ECG on the stratification and clincial management of syncope risk is emerging.
关键词
晕厥/人工智能/心电图/诊断Key words
Syncope/Artificial intelligence/Electrocardiogram/Diagnosis引用本文复制引用
基金项目
国家自然科学基金面上项目(82170327)
出版年
2024
NETL
NSTL
万方数据