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Updated: May 6, 2026

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RAMAS-Net:一个模块优化的卷积网络模型,用于在心声学中识别大动脉狭窄

Yejia Gan1, Wanzhong Huang2, Yan Deng3

  • 1Department of Information and Management, Guangxi Medical University, Nanning, China.

Frontiers in medicine
|May 13, 2025
PubMed
概括

一个新的深度学习模型,RSMAS-Net,通过回声心脏图准确识别大动脉狭窄 (AS) 和其严重程度. 这种人工智能工具提高了诊断精度,有助于评估膜心脏病的临床决策.

关键词:
大动脉门狭窄症人工智能的人工智能是人工智能.心血管疾病心血管疾病深度学习是一种深度学习.超声心电图 (Echocardiography) 是一种心声回声仪.跨胸腔回声心脏成像 (Transthoracic-Echocardiography) 是一种心脏成像技术.

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