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English(EN) StrokeTimer: Robust Representation Learning for Ischemic Stroke Onset-Time Estimation from Non-contrast CT

StrokeTimer 使用 AI 估算缺血性卒中发病时间

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了 StrokeTimer，一个使用非对比增强 CT 扫描来估算缺血性卒中发病时间的新框架。该方法采用自监督解耦和能量引导的对比学习，即使在数据不平衡和扫描仪类型各异的情况下，也能识别出卒中的细微迹象。在多中心数据集上，StrokeTimer 的宏观 AUC 达到 0.69，宏观 F1 分数达到 0.57，显著优于现有的基线方法。 AI

影响 通过提供更准确的发病时间估算，有潜力改善急性缺血性卒中的治疗决策。

排序理由 该集群包含一篇详细介绍用于特定医疗应用的 AI 模型的研究论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

StrokeTimer 使用 AI 估算缺血性卒中发病时间

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该集群包含一篇详细介绍用于特定医疗应用的 AI 模型的研究论文。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Weiru Wang, Susanne G. H. Olthuis, Elizaveta Lavrova, Robert J. van Oostenbrugge, Charles B. L. M. Majoie, Wim H. van Zwam, Ruisheng Su ·

    StrokeTimer：基于非对比CT的缺血性卒中发病时间估计的鲁棒表示学习

    arXiv:2606.04722v1 Announce Type: new Abstract: Ischemic stroke is a major global disease. Treatment decisions are highly time-sensitive, as eligibility for reperfusion therapies relies on the interval between stroke onset and intervention. However, the true onset time is often u…

  2. arXiv cs.CV TIER_1 English(EN) · Ruisheng Su ·

    StrokeTimer：基于非对比CT的缺血性卒中发病时间估计的鲁棒表示学习

    Ischemic stroke is a major global disease. Treatment decisions are highly time-sensitive, as eligibility for reperfusion therapies relies on the interval between stroke onset and intervention. However, the true onset time is often uncertain in clinical practice, necessitating ima…

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