Development and validation of a novel multimodal deep learning model integrating histopathology, radiology, and clinical data to predict primary non-response to infliximab in patients with Crohn’s disease
The study developed a multimodal deep learning model accurately predicting IFX primary non-response, offering a tool to guide individualized therapy and improve CD outcomes.
Authors
- Xiaomin Wu (ORCID: https://orcid.org/0009-0009-7390-8574)
- Ziyin Ye (ORCID: https://orcid.org/0000-0001-9530-3407)
- Zishan Liu (ORCID: https://orcid.org/0000-0002-6066-1092)
- Bingsheng Huang (ORCID: https://orcid.org/0000-0002-1183-7506)
- Xiaoyu Duan (ORCID: https://orcid.org/0000-0002-6324-354X)
- Lihui Zhang (ORCID: https://orcid.org/0000-0001-7308-5277)
- Haipeng Wang (ORCID: https://orcid.org/0000-0003-1912-7143)
- Shanshan Xiong
- Yanling Wei
- Xuehua Li (ORCID: https://orcid.org/0000-0002-7476-2644)
- Minhu Chen
- Ren Mao
- Yu Wang (ORCID: https://orcid.org/0000-0001-8697-2940)
Institutions
- Army Medical University (CN)
- Sun Yat-sen University (CN)
- Shenzhen University (CN)
- Daping Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Shenzhen University Health Science Center (CN)
Publication Details
- Journal
- Journal of Crohn s and Colitis
- Published
- 2025-11-24
- DOI
- https://doi.org/10.1093/ecco-jcc/jjaf206
- Primary Topic
- Inflammatory Bowel Disease
- Type
- article
- Field-Weighted Citation Impact
- 0.00