English(EN) HRVConformer: Neonatal Hypoxic-Ischemic Encephalopathy Classification from the Heart Rate signals

深度学习模型利用心率信号对新生儿HIE进行分类

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-27 04:00

研究人员开发了HRVConformer，这是一种新颖的深度学习模型，旨在利用心率信号对新生儿缺氧缺血性脑病（HIE）进行分类。该架构结合了用于局部特征提取的卷积层和用于全局上下文的Transformer注意力机制，对原始心率数据进行端到端处理。HRVConformer在一个大型数据集上进行训练，在测试集上取得了83.23%的AUC和74.56%的准确率，优于现有的基线模型，为自动评估HIE提供了有前景的进展。 AI

影响这项研究引入了一种新的深度学习架构，可以提高新生儿缺氧缺血性脑病诊断的准确性和自动化水平。

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arXiv cs.AI TIER_1 English(EN) · Shuwen Yu, William P Marnane, Geraldine B. Boylan, Gordon Lightbody · 2026-05-27 04:00

HRVConformer：基于心率信号的新生儿缺氧缺血性脑病分类

arXiv:2605.26190v1 Announce Type: cross Abstract: This paper presents the HRVConformer, a novel deep learning architecture for the classification of hypoxic-ischemic encephalopathy (HIE) using the instantaneous heart rate (HR) signal. Unlike conventional approaches that rely on h…

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HRVConformer：基于心率信号的新生儿缺氧缺血性脑病分类

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