Multi-omics prognostic marker discovery and survival modelling: a case study on multi-cancer survival analysis of women’s specific tumours
8.0
来源：
Nature
关键字：
neural coding
发布时间：
2025-10-21 19:40
摘要：
PRISM (PRognostic marker Identification and Survival Modelling through Multi-omics Integration) is a comprehensive framework designed to enhance cancer survival prediction by integrating multi-omics data. It systematically evaluates feature selection methods and survival models, revealing unique combinations of omics modalities that improve prognostic accuracy. Applied to TCGA cohorts of women's cancers, PRISM identifies concise biomarker signatures, promoting clinical feasibility and precision oncology. This innovative approach addresses the challenges of high-dimensional data, offering a scalable solution for personalized treatment strategies.
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1.0分
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1.5分
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关键证据
PRISM systematically evaluates various feature selection methods and survival models.
PRISM revealed that cancer types benefit from unique combinations of omics modalities.
The framework improves survival prediction, aiding patient stratification and personalized treatment.
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AI评分总结
PRISM (PRognostic marker Identification and Survival Modelling through Multi-omics Integration) is a comprehensive framework designed to enhance cancer survival prediction by integrating multi-omics data. It systematically evaluates feature selection methods and survival models, revealing unique combinations of omics modalities that improve prognostic accuracy. Applied to TCGA cohorts of women's cancers, PRISM identifies concise biomarker signatures, promoting clinical feasibility and precision oncology. This innovative approach addresses the challenges of high-dimensional data, offering a scalable solution for personalized treatment strategies.