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English(EN) MM-Net: A Multimodal Multi-Task Network for Sleep Staging and Sleep Apnea Assessment After Ischemic Stroke

新的MM-Net模型增强了卒中后睡眠分期和呼吸暂停评估

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了MM-Net，这是一种新颖的多模态多任务网络，旨在提高睡眠分期和睡眠呼吸暂停评估的准确性，特别是在经历缺血性卒中的患者中。该网络通过交叉注意力和共享时间建模，融合了适应性脑电图-眼电图表示与心肺呼吸道特征，解决了现有方法的挑战。MM-Net在iSLEEPS数据集上表现出卓越的性能，达到了76.3%的睡眠分期准确率和0.825的呼吸事件AUC，并在Sleep-EDF和ISRUC-I数据集上也取得了优异的结果。 AI

影响 这项研究可能为卒中患者的睡眠障碍提供更准确和集成的诊断工具。

排序理由 该集群包含一篇详细介绍用于特定医疗应用的新模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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新的MM-Net模型增强了卒中后睡眠分期和呼吸暂停评估

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该集群包含一篇详细介绍用于特定医疗应用的新模型的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Md Wahiduzzaman Suva, Esm E Moula Chowdhury Abha, Md Imtiaj Alam Sajin, Md Iftekharul Mobin, Jia Uddin ·

    MM-Net：一种用于缺血性中风后睡眠分期和睡眠呼吸暂停评估的多模态多任务网络

    arXiv:2610.36583v1 Announce Type: cross Abstract: Automated polysomnography after ischemic stroke is challenging because of altered sleep-related neural activity and concurrent respiratory disturbances. Existing stroke-specific approaches mainly address sleep-stage classification…

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