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English(EN) REST: Reliability-Guided Spatial Transcriptomics Supervision for Gene Expression Prediction from Histopathological HE-Stained Images

新的 REST 框架可从组织图像预测基因表达

研究人员开发了一个名为 REST(可靠性引导空间转录组学监督)的新框架,用于从组织病理学 HE 染色图像预测基因表达。该方法使用生物程序库来指导过程,估计空间转录组学数据的可靠性并相应地重新加权对齐。REST 旨在提供组织结构内的分子信息,这对于癌症诊断和表征至关重要,并且与现有的病理学基础模型相比,其性能更优。 AI

影响 这项研究通过直接从组织图像实现更准确的分子谱分析,有可能改善癌症的诊断和治疗。

排序理由 该集群描述了一篇详细介绍从组织病理学图像预测基因表达的新颖方法的新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 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 REST 框架可从组织图像预测基因表达

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该集群描述了一篇详细介绍从组织病理学图像预测基因表达的新颖方法的新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Lanfeng Zhong, Xiangyu Sun, Guixuan Xu, Rongzhao Zhang, Jie Xu, Shaoting Zhang, Guotai Wang ·

    REST:用于从组织病理学HE染色图像预测基因表达的可靠性引导空间转录组学监督

    arXiv:2610.26988v1 Announce Type: new Abstract: Histopathology is central to cancer diagnosis, but morphology in Hematoxylin and Eosin (HE)-stained images does not directly reveal the molecular states that characterize disease heterogeneity and inform tumor characterization, prog…