An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data

An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data

Abstract Background The accurate early-stage diagnosis of gallbladder cancer (GBC) is regarded as one of the major challenges in the field of oncology. However, few studies have focused on the comprehensive classification of GBC based on multiple modalities. This study aims to develop a comprehensiv...

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Bibliographic Details
Main Authors: Huiyu Zhao, Chuang Miao, Yidi Zhu, Yijun Shu, Xiangsong Wu, Ziming Yin, Xiao Deng, Wei Gong, Ziyi Yang, Weiwen Zou
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Cancer
Subjects:
Gallbladder cancer
Deep learning
Machine learning
Multi-modality medical data
Interpretable
Online Access:https://doi.org/10.1186/s12885-025-14462-9
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https://doi.org/10.1186/s12885-025-14462-9

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