Integrated Radiomics and Machine Learning Approach for RAS Mutation Status Prediction in Colorectal Liver Metastases

Name: Integrated Radiomics and Machine Learning Approach for RAS Mutation Status Prediction in Colorectal Liver Metastases
Creator: Zenodo
Published: 2025-10-15T13:18:08+08:00

Zenodo2025-10-15 更新2026-05-26 收录

影像组学

基因突变预测

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https://zenodo.org/doi/10.5281/zenodo.17359772 数据链接链接失效反馈

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资源简介：

I uploaded the the robust Radiomics features extracted in the study "Integrated Radiomics and Machine Learning Approach for RAS Mutation Status Prediction in Colorectal Liver Metastases". Authors: Vincenza Granata1, Roberta Fusco1*, Sergio Venanzio Setola1, Federica De Muzio2, Maria Chiara Brunese3, Antonio Avallone4, Alessandro Ottaiano4, Andrea Belli5, Francesco Izzo5, Antonella Petrillo1 1 Division of Radiology, “Istituto Nazionale Tumori IRCCS Fondazione Pascale – IRCCS di Napoli”, Naples, Italy 2 Pineta Grande Ospital, Castel Volturno, Naples, Italy3 Department of Medicine and Health Sciences V. Tiberio, University of Molise, Campobasso, Italy.4 Clinical Sperimental Abdominal Oncology Unit, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, Naples, Italy.5 Division of Epatobiliary Surgical Oncology, Istituto Nazionale Tumori IRCCS Fondazione Pascale—IRCCS di Napoli, Naples, Italy

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Zenodo

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2025-10-15

Integrated Radiomics and Machine Learning Approach for RAS Mutation Status Prediction in Colorectal Liver Metastases

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