Interpretable multimodal deep learning improves postoperative risk stratification in intrahepatic cholangiocarcinoma in multicentre cohorts.

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Title: Interpretable multimodal deep learning improves postoperative risk stratification in intrahepatic cholangiocarcinoma in multicentre cohorts.
Authors: Wan M; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Ding Y; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Wang Y; Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China., Jia Y; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Wu S; The First Clinical School of Medicine, Zhengzhou University, Zhengzhou, China., Qu W; Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China., Xu Y; Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China., Fu W; Department of Hepatobiliary Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China., Timko MP; Departments of Biology and Public Health Sciences, University of Virginia, Charlottesville, VA, USA., Wan L; Department of Pharmacological Sciences, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, USA., Ying L; Department of Medicine, Monash University, Clayton, VIC, Australia., Ye C; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Chen R; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Li Q; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., He Y; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Xu K; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Xu N; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China., Chen J; Department of Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China. chenjinzhang@smu.edu.cn., Zheng D; Department of Oncology, Shunde Hospital, Southern Medical University, Shunde, China. zhengdayong@hotmail.com., Shen Y; Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. yifeishen@zju.edu.cn.; Department of Bioinformatics and Computational Biology, MD Anderson Cancer Center, Houston, TX, USA. yifeishen@zju.edu.cn., Ruan J; Department of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, & Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, Hangzhou, China. software233@zju.edu.cn.
Source: NPJ digital medicine [NPJ Digit Med] 2025 Dec 29; Vol. 9 (1), pp. 95. Date of Electronic Publication: 2025 Dec 29.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2398-6352
DOI:10.1038/s41746-025-02282-x