Multi-cohort study in gastric cancer to develop CT-based radiomic models to predict pathological response to neoadjuvant immunotherapy

Multi-cohort study in gastric cancer to develop CT-based radiomic models to predict pathological response to neoadjuvant immunotherapy

Abstract Background Neoadjuvant immunotherapy has been shown to improve survival in patients with gastric cancer. This study sought to develop and validate a radiomics-based machine learning (ML) model for patients with locally advanced gastric cancer (LAGC), specifically to predict whether patients...

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Main Authors: Ze-Ning Huang, Hao-Xiang Zhang, Yu-Qin Sun, Xing-Qi Zhang, Yi-Fen Lin, Cai-Ming Weng, Chao-Hui Zheng, Ping-Li, Jia-Bin Wang, Qi-Yue Chen, Long-Long Cao, Mi Lin, Ru-Hong Tu, Chang-Ming Huang, Jian-Xian Lin, Jian-Wei Xie
Format: Article
Language:English
Published: BMC 2025-03-01
Series:Journal of Translational Medicine
Subjects:
Radiomics
Machine learning
Neoadjuvant therapy
Immunotherapy
Prediction model
Online Access:https://doi.org/10.1186/s12967-025-06363-z
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https://doi.org/10.1186/s12967-025-06363-z

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