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SAF-Net: 使用多视角超声心动图检测心肌梗死的自注意融合网络

💡 原文中文，约400字，阅读约需1分钟。

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内容提要

SAF-Net是一种新型视图融合模型，用于从多视角超声心动图记录中检测心肌梗死。该模型利用自注意机制学习提取的特征向量中的依赖关系，实现了较高的精确度、敏感度和准确度。

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