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Objective: This study classified hematoxylin and eosin (H&amp;E) histological images of ulcerative colitis, normal colon, and colorectal cancer using artificial intelligence (deep learning). Methods: A convolutional neural network (CNN) was designed and trained to classify the three types of diagnosis, including 35 cases of ulcerative colitis (n = 9281 patches), 21 colon control (n = 12,246), and 18 colorectal cancer (n = 63,725). The data were partitioned into training (70%) and validation sets (10%) for training the network, and a test set (20%) to test the performance on the new data. The CNNs included transfer learning from ResNet-18, and a comparison with other CNN models was performed. Explainable artificial intelligence for computer vision was used with the Grad-CAM technique, and additional LAIR1 and TOX2 immunohistochemistry was performed in ulcerative colitis to analyze the immune microenvironment. Results: Conventional clinicopathological analysis showed that steroid-requiring ulcerative colitis was characterized by higher endoscopic Baron and histologic Geboes scores and LAIR1 expression in the lamina propria, but lower TOX2 expression in isolated lymphoid follicles (all p values &lt; 0.05) compared to mesalazine-responsive ulcerative colitis. The CNN classification accuracy was 99.1% for ulcerative colitis, 99.8% for colorectal cancer, and 99.1% for colon control. The Grad-CAM heatmap confirmed which regions of the images were the most important. The CNNs also differentiated between steroid-requiring and mesalazine-responsive ulcerative colitis based on H&amp;E, LAIR1, and TOX2 staining. Additional classification of 10 new cases of colorectal cancer (adenocarcinoma) were correctly classified. Conclusions: CNNs are especially suited for image classification in conditions such as ulcerative colitis and colorectal cancer; LAIR1 and TOX2 are relevant immuno-oncology markers in ulcerative colitis.<\/jats:p>","DOI":"10.3390\/cancers16244230","type":"journal-article","created":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T03:59:43Z","timestamp":1734580783000},"page":"4230","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Ulcerative Colitis, LAIR1 and TOX2 Expression, and Colorectal Cancer Deep Learning Image Classification Using Convolutional Neural Networks"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6129-8299","authenticated-orcid":false,"given":"Joaquim","family":"Carreras","sequence":"first","affiliation":[{"name":"Department of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9807-2875","authenticated-orcid":false,"given":"Giovanna","family":"Roncador","sequence":"additional","affiliation":[{"name":"Monoclonal Antibodies Unit, Spanish National Cancer Research Center (CNIO), Melchor Fernandez Almagro 3, 28029 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1402-0868","authenticated-orcid":false,"given":"Rifat","family":"Hamoudi","sequence":"additional","affiliation":[{"name":"Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"},{"name":"Biomedically Informed Artificial Intelligence Laboratory (BIMAI-Lab), University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"},{"name":"Center of Excellence for Precision Medicine, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"},{"name":"Division of Surgery and Interventional Science, University College London, London NW3 2PF, UK"},{"name":"ASPIRE Precision Medicine Research Institute Abu Dhabi, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7247238","DOI":"10.1155\/2019\/7247238","article-title":"A Comprehensive Review and Update on the Pathogenesis of Inflammatory Bowel Disease","volume":"2019","author":"Guan","year":"2019","journal-title":"J. Immunol. 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