Deep learning-based multimodal approach for non-invasive prediction and prognostic analysis of immune and angiogenic biomarkers in extrahepatic cholangiocarcinoma

Our findings highlighted the potential of integrating DL and radiomics for non-invasive, preoperative biomarker profiling, offering a promising tool for personalized treatment strategies and improved clinical decision-making in eCCA.

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Publication Details

Journal
Frontiers in Immunology
Published
2026-01-13
DOI
https://doi.org/10.3389/fimmu.2025.1658122
Primary Topic
Cholangiocarcinoma and Gallbladder Cancer Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Deep learning-based multimodal approach for non-invasive prediction and prognostic analysis of immune and angiogenic biomarkers in extrahepatic cholangiocarcinoma

Jian Shu, Yue Shu, Ruidan Yang, Jiong Liu et al.
Frontiers in Immunology
Cholangiocarcinoma and Gallbladder Cancer Studies
article

Deep learning-based multimodal approach for non-invasive prediction and prognostic analysis of immune and angiogenic biomarkers in extrahepatic cholangiocarcinoma

Jian Shu, Yue Shu, Ruidan Yang, Jiong Liu, Yong Tang, Zhitao Cheng, Yinfei Fan
article en

Abstract

Our findings highlighted the potential of integrating DL and radiomics for non-invasive, preoperative biomarker profiling, offering a promising tool for personalized treatment strategies and improved clinical decision-making in eCCA.

Frontiers in ImmunologyVol. 16
University of Electronic Science and Technology of China (CN), Affiliated Hospital of Southwest Medical University (CN), First Affiliated Hospital of Sichuan Medical University (CN), Chongqing Institute of Green and Intelligent Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 90%
Cholangiocarcinoma and Gallbladder Cancer Studies
DOIOpen Access PDFOpenAlex
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