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This paper is in the following e-collection/theme issue:

Machine Learning (2345) Clinical Information and Decision Making (2186) Decision Support for Health Professionals (1729) Ontologies, Classifications, and Coding (364) Imaging Informatics (360) Infectious Diseases (non-STD/STI) (1777) Gastroenterology and Hepatology (153)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64987, first published .
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Enhancing the Predictions of Cytomegalovirus Infection in Severe Ulcerative Colitis Using a Deep Learning Ensemble Model: Development and Validation Study

Enhancing the Predictions of Cytomegalovirus Infection in Severe Ulcerative Colitis Using a Deep Learning Ensemble Model: Development and Validation Study

Authors of this article:

Jeong Heon Kim1 Author Orcid Image ;   A Reum Choe2 Author Orcid Image ;   Ju Ran Byeon2 Author Orcid Image ;   Yehyun Park2 Author Orcid Image ;   Eun Mi Song2 Author Orcid Image ;   Seong-Eun Kim2 Author Orcid Image ;   Eui Sun Jeong2 Author Orcid Image ;   Rena Lee3 Author Orcid Image ;   Jin Sung Kim1 Author Orcid Image ;   So Hyun Ahn4 Author Orcid Image ;   Sung Ae Jung2 Author Orcid Image
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Journals

  1. Liang H, Tian Y, Ruan G, Bai X, Han W, Fu X, Wang Y, Shi J, Sun Y, Wu J, Guo C, Yang H. Artificial intelligence-based multimodal model for the identification of ulcerative colitis with concomitant cytomegalovirus colitis. Therapeutic Advances in Gastroenterology 2025;18 View
  2. Yang Z, Yao J, Zhao X, Xu Y, Chen Y, Chen T, Jian Y, Li M. Multi‐omics biomarkers for intestinal infection and inflammation in inflammatory bowel disease: Current evidence, translational challenges, and diagnostic opportunities. Interdisciplinary Medicine 2026 View