{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T06:05:51Z","timestamp":1770962751309,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,10,8]],"date-time":"2021-10-08T00:00:00Z","timestamp":1633651200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005416","name":"The Research Council of Norway","doi-asserted-by":"publisher","award":["296599"],"award-info":[{"award-number":["296599"]}],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Acute intestinal ischemia is a life-threatening condition. The current gold standard, with evaluation based on visual and tactile sensation, has low specificity. In this study, we explore the feasibility of using machine learning models on images of the intestine, to assess small intestinal viability. A digital microscope was used to acquire images of the jejunum in 10 pigs. Ischemic segments were created by local clamping (approximately 30 cm in width) of small arteries and veins in the mesentery and reperfusion was initiated by releasing the clamps. A series of images were acquired once an hour on the surface of each of the segments. The convolutional neural network (CNN) has previously been used to classify medical images, while knowledge is lacking whether CNNs have potential to classify ischemia-reperfusion injury on the small intestine. We compared how different deep learning models perform for this task. Moreover, the Shapley additive explanations (SHAP) method within explainable artificial intelligence (AI) was used to identify features that the model utilizes as important in classification of different ischemic injury degrees. To be able to assess to what extent we can trust our deep learning model decisions is critical in a clinical setting. A probabilistic model Bayesian CNN was implemented to estimate the model uncertainty which provides a confidence measure of our model decisions.<\/jats:p>","DOI":"10.3390\/s21196691","type":"journal-article","created":{"date-parts":[[2021,10,10]],"date-time":"2021-10-10T21:37:49Z","timestamp":1633901869000},"page":"6691","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Automatic Prediction of Ischemia-Reperfusion Injury of Small Intestine Using Convolutional Neural Networks: A Pilot Study"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5765-1395","authenticated-orcid":false,"given":"Jie","family":"Hou","sequence":"first","affiliation":[{"name":"Department of Physics, University of Oslo, Sem S\u00e6lands vei 24, 0371 Oslo, Norway"},{"name":"Department of Clinical and Biomedical Engineering, Oslo University Hospital, 0372 Oslo, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Runar","family":"Strand-Amundsen","sequence":"additional","affiliation":[{"name":"Department of Clinical and Biomedical Engineering, Oslo University Hospital, 0372 Oslo, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Tronstad","sequence":"additional","affiliation":[{"name":"Department of Clinical and Biomedical Engineering, Oslo University Hospital, 0372 Oslo, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan Olav","family":"H\u00f8getveit","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Oslo, Sem S\u00e6lands vei 24, 0371 Oslo, Norway"},{"name":"Department of Clinical and Biomedical Engineering, Oslo University Hospital, 0372 Oslo, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"\u00d8rjan Gr\u00f8ttem","family":"Martinsen","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Oslo, Sem S\u00e6lands vei 24, 0371 Oslo, Norway"},{"name":"Department of Clinical and Biomedical Engineering, Oslo University Hospital, 0372 Oslo, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3511-5815","authenticated-orcid":false,"given":"Tor Inge","family":"T\u00f8nnessen","sequence":"additional","affiliation":[{"name":"Department of Emergencies and Critical Care, Oslo University Hospital, 0424 Oslo, Norway"},{"name":"Institute of Clinical Medicine, University of Oslo, 0424 Oslo, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/j.amjsurg.2020.01.042","article-title":"Techniques for intraoperative evaluation of bowel viability in mesenteric ischemia: A review","volume":"220","author":"Bryski","year":"2020","journal-title":"Am. 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