{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:43:59Z","timestamp":1785545039859,"version":"3.56.0"},"reference-count":45,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Med Inform"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Cytomegalovirus (CMV) reactivation in patients with severe ulcerative colitis (UC) leads to worse outcomes; yet, early detection remains challenging due to the reliance on time-intensive biopsy procedures.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study explores the use of deep learning to differentiate CMV from severe UC through endoscopic imaging, offering a potential noninvasive diagnostic tool.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n We analyzed 86 endoscopic images using an ensemble of deep learning models, including DenseNet (Densely Connected Convolutional Network) 121 pretrained on ImageNet. Advanced preprocessing and test-time augmentation (TTA) were applied to optimize model performance. The models were evaluated using metrics such as accuracy, precision, recall,\n F<\/jats:italic>\n 1<\/jats:sub>\n -score, and area under the curve.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The ensemble approach, enhanced by TTA, achieved high performance, with an accuracy of 0.836, precision of 0.850, recall of 0.904, and an\n F<\/jats:italic>\n 1<\/jats:sub>\n -score of 0.875. Models without TTA showed a significant drop in these metrics, emphasizing TTA\u2019s importance in improving classification performance.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n This study demonstrates that deep learning models can effectively distinguish CMV from severe UC in endoscopic images, paving the way for early, noninvasive diagnosis and improved patient care.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/64987","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T02:30:06Z","timestamp":1741660206000},"page":"e64987-e64987","source":"Crossref","is-referenced-by-count":4,"title":["Enhancing the Predictions of Cytomegalovirus Infection in Severe Ulcerative Colitis Using a Deep Learning Ensemble Model: Development and Validation Study"],"prefix":"10.2196","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9321-3117","authenticated-orcid":false,"given":"Jeong 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