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English(EN) EvoSurv: Evolution-Aware Multimodal Survival Modeling Reveals Complementary Prognostic Signals

新的EvoSurv模型整合基因组进化以预测癌症生存率

研究人员开发了EvoSurv,一个新颖的多模态生存框架,它整合了来自基因组改变的进化信息与临床和RNA表达数据,以预测癌症生存率。该框架使用一种称为eTime的8维进化表示,在六个TCGA癌症队列中表现出优越的性能,其平均一致性指数高于现有方法。研究还发现,进化特征,特别是在头颈部鳞状细胞癌中的T>G取代,提供了超越传统临床和分子预测因子的重要预后价值。 AI

影响 这项研究可能通过将进化基因组数据纳入预测模型,从而实现更准确的癌症预后。

排序理由 该集群包含一篇详细介绍新计算模型及其评估的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的EvoSurv模型整合基因组进化以预测癌症生存率

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该集群包含一篇详细介绍新计算模型及其评估的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Wei Wang, Po-Yu Liang, Jun Bai ·

    EvoSurv:进化感知多模态生存建模揭示互补预后信号

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