Artificial intelligence-based multimodal model for the identification of ulcerative colitis with concomitant cytomegalovirus colitis
AI application offers a promising way to enhance early identification of UC with CMV colitis. The multimodal model combining clinical and endoscopic data can assist clinicians in accurate and timely diagnosis.
Authors
- Xiangling Fu (ORCID: https://orcid.org/0000-0002-1492-2829)
- Xiaoyin Bai (ORCID: https://orcid.org/0000-0002-9092-7592)
- Haozheng Liang
- Yinghao Sun
- Chenyi Guo (ORCID: https://orcid.org/0000-0002-8222-5179)
- Hong Yang (ORCID: https://orcid.org/0000-0002-2986-7324)
- Ji Wu (ORCID: https://orcid.org/0000-0002-8073-5319)
- Yu-Hang Wang (ORCID: https://orcid.org/0000-0003-1929-2384)
- Wei Han (ORCID: https://orcid.org/0000-0001-6848-6439)
- Yuxuan Tian
- Jialin Shi (ORCID: https://orcid.org/0000-0001-9629-3706)
- Gechong Ruan
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- University of Science and Technology Beijing (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Therapeutic Advances in Gastroenterology
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1177/17562848251364194
- Citations
- 1
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 1.36