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English(EN) Predicting one-year clinical instability and mortality in heart failure patients using sequence modeling

序列模型预测心力衰竭患者的不稳定性和死亡率

研究人员开发了序列模型,利用电子健康记录来预测心力衰竭患者一年内的临床不稳定性和死亡率。该研究对瑞典一个由超过42,000名患者组成的队列进行,采用了一种将结构化电子健康记录数据转化为患者序列的框架。Llama等模型表现出强大的预测能力,优于传统方法,并且即使在临床概念或训练数据有限的情况下也显示出稳健性。 AI

影响 展示了序列模型在改善患者风险分层和指导医疗保健中的出院计划方面的潜力。

排序理由 这是一篇详细介绍序列模型在临床预测中新应用的学术论文。

在 arXiv cs.LG 阅读 →

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序列模型预测心力衰竭患者的不稳定性和死亡率

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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Falk Dippel, Yinan Yu, Annika Rosengren, Martin Lindgren, Christina E. Lundberg, Erik Aerts, Martin Adiels, Helen Sj\"oland ·

    使用序列模型预测心力衰竭患者一年的临床不稳定性和死亡率

    arXiv:2511.16839v3 Announce Type: replace Abstract: Heart failure (HF) discharge planning depends on identifying patients at risk of deterioration or death, yet accurate prediction from routinely collected electronic health records (EHRs) remains challenging. We developed and val…