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通过人工智能增强的综合评估,在心声回声学中对主动脉狭窄连续体进行综合评估

Jiesuck Park¹, Jiyeon Kim², Jaeik Jeon³

¹Cardiovascular Center and Division of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Gyeonggi, Republic of Korea; Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.

|January 22, 2025

概括

一个人工智能 (AI) 系统使用心声学准确评估大动脉狭窄 (AS),提供宝贵的预后见解. 这种人工智能工具在各种临床环境中是有效的,包括那些资源有限的临床环境.

科学领域:

心脏病学心脏病学
人工智能的人工智能
医疗成像医学成像

背景情况:

胸外回声心电图 (TTE) 是主动脉狭窄 (AS) 诊断的标准,但需要专业知识和资源.
一个基于人工智能 (AI) 的系统被开发来解决AS评估中的这些局限性.

研究的目的:

开发和验证人工智能系统,以准确和具有预后价值的AS评估.
评估AI系统在资源有限和先进的临床环境中的有效性.

主要方法:

一个双通道的人工智能系统是使用大型心声回声数据集创建的.
方法包括深度学习 (DL) 算法用于AS连续评估和自动化传统AS参数测量.
验证是在内部,外部和时间上不同的数据集上进行的.

主要成果:

对于AS连续性的DL指数 (DLi-ASc) 显示了所有AS阶段的优异歧视 (AUC为0.91-0.99).
DLi-ASc是复合心血管终点的独立预测因子.
自动化常规AS参数测量实现了AS分期的高精度和与手动测量相比较的预后值.

结论:

基于人工智能的系统提供了准确且具有预后意义的AS评估.
该系统适合在各种临床环境中部署,增强AS诊断和管理.

关键词:

大动脉狭窄症大动脉狭窄症人工智能的人工智能是人工智能.诊断的准确性诊断的准确性心声回声扫描 (Echocardiography) 是一种心声回声扫描.预测值的预测值是指预测值的预测值.

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