{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T22:32:49Z","timestamp":1789770769718,"version":"4.0.1"},"reference-count":47,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,10,10]],"date-time":"2023-10-10T00:00:00Z","timestamp":1696896000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100005205","name":"Janssen Research & Development","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005205","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,4,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aims<\/jats:title>\n                    <jats:p>Histological disease activity in inflammatory bowel disease [IBD] is associated with clinical outcomes and is an important endpoint in drug development. We developed deep learning models for automating histological assessments in IBD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Histology images of intestinal mucosa from phase 2 and phase 3 clinical trials in Crohn\u2019s disease [CD] and ulcerative colitis [UC] were used to train artificial intelligence [AI] models to predict the Global Histology Activity Score [GHAS] for CD and Geboes histopathology score for UC. Three AI methods were compared. AI models were evaluated on held-back testing sets, and model predictions were compared against an expert central reader and five independent pathologists.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The model based on multiple instance learning and the attention mechanism [SA-AbMILP] demonstrated the best performance among competing models. AI-modelled GHAS and Geboes subgrades matched central readings with moderate to substantial agreement, with accuracies ranging from 65% to 89%. Furthermore, the model was able to distinguish the presence and absence of pathology across four selected histological features, with accuracies for colon in both CD and UC ranging from 87% to 94% and for CD ileum ranging from 76% to 83%. For both CD and UC and across anatomical compartments [ileum and colon] in CD, comparable accuracies against central readings were found between the model-assigned scores and scores by an independent set of pathologists.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Deep learning models based upon GHAS and Geboes scoring systems were effective at distinguishing between the presence and absence of IBD microscopic disease activity.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ecco-jcc\/jjad171","type":"journal-article","created":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T23:22:07Z","timestamp":1696893727000},"page":"604-614","source":"Crossref","is-referenced-by-count":47,"title":["Deep Learning Models Capture Histological Disease Activity in Crohn\u2019s Disease and Ulcerative Colitis with High Fidelity"],"prefix":"10.1093","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8543-5200","authenticated-orcid":false,"given":"Dawid","family":"Rymarczyk","sequence":"first","affiliation":[{"name":"AI Lab, Ardigen SA , Krak\u00f3w , Poland"},{"name":"Faculty of Mathematics and Computer Science, Jagiellonian University , Krak\u00f3w , Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiwei","family":"Schultz","sequence":"additional","affiliation":[{"name":"Data Science & Digital Health, Janssen Research & Development, LLC , Spring House, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adriana","family":"Borowa","sequence":"additional","affiliation":[{"name":"AI Lab, Ardigen SA , Krak\u00f3w , Poland"},{"name":"Faculty of Mathematics and Computer Science, Jagiellonian University , Krak\u00f3w , Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua 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