English(EN) Real-World Multi-Modal and Longitudinal Lung Cancer Dataset

新的肺癌数据集整合了影像、临床和基因组数据

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-07 04:00

研究人员推出了一款新的多模态肺癌研究数据集，旨在模拟真实世界数据的复杂性。该数据集包含来自全切片图像、CT扫描和PET扫描的影像，以及 1365 名患者的临床、转录组和纵向随访信息。数据在不同模态之间存在显著的缺失，使其适用于研究鲁棒的多模态融合策略。在生存预测任务上的初步基准测试表明，即使存在大量缺失数据，整合这些多样化的数据源也能提高预测性能。 AI

影响该数据集有望通过提供现实、复杂的数据基础，加速多模态人工智能在医学诊断和预后方面的研究。

排序理由该集群描述了在arXiv上发布的新数据集和基准测试，属于研究类别。[lever_c_demoted from research: ic=1 ai=1.0]

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Newsworthiness bucket: Tool; 该集群描述了在arXiv上发布的新数据集和基准测试，属于研究类别。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.CV TIER_1 English(EN) · Rita Cordeiro Mendes, Maria Rita Fonseca Verdelho, Carlos Santiago, Catarina Barata · 2026-09-07 04:00

真实世界多模态和纵向肺癌数据集

arXiv:2609.05202v1 Announce Type: cross Abstract: Multi-modal learning has demonstrated strong potential in medical applications by integrating heterogeneous data sources such as medical imaging, clinical records, and genomics to improve predictive performance and support clinica…

本文如何被排名

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真实世界多模态和纵向肺癌数据集

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