{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T05:57:58Z","timestamp":1790834278724,"version":"4.1.0"},"reference-count":76,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T00:00:00Z","timestamp":1684454400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background: Artificial Intelligence (AI)-based Deep Neural Networks (DNNs) can handle a wide range of applications in image analysis, ranging from automated segmentation to diagnostic and prediction. As such, they have revolutionized healthcare, including in the liver pathology field. Objective: The present study aims to provide a systematic review of applications and performances provided by DNN algorithms in liver pathology throughout the Pubmed and Embase databases up to December 2022, for tumoral, metabolic and inflammatory fields. Results: 42 articles were selected and fully reviewed. Each article was evaluated through the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool, highlighting their risks of bias. Conclusions: DNN-based models are well represented in the field of liver pathology, and their applications are diverse. Most studies, however, presented at least one domain with a high risk of bias according to the QUADAS-2 tool. Hence, DNN models in liver pathology present future opportunities and persistent limitations. To our knowledge, this review is the first one solely focused on DNN-based applications in liver pathology, and to evaluate their bias through the lens of the QUADAS2 tool.<\/jats:p>","DOI":"10.3390\/diagnostics13101799","type":"journal-article","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T09:23:10Z","timestamp":1684488190000},"page":"1799","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Artificial Intelligence-Based Opportunities in Liver Pathology\u2014A Systematic Review"],"prefix":"10.3390","volume":"13","author":[{"given":"Pierre","family":"Allaume","sequence":"first","affiliation":[{"name":"Department of Pathology CHU de Rennes, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"No\u00e9mie","family":"Rabilloud","sequence":"additional","affiliation":[{"name":"Impact TEAM, Laboratoire Traitement du Signal et de l\u2019Image (LTSI) INSERM, Rennes 1 University, Pontchaillou Hospital, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9779-8041","authenticated-orcid":false,"given":"Bruno","family":"Turlin","sequence":"additional","affiliation":[{"name":"Department of Pathology CHU de Rennes, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"},{"name":"Research Unit n\u00b0UMR1341 NuMeCan\u2013Nutrition, M\u00e9tabolismes et Cancer, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edouard","family":"Bardou-Jacquet","sequence":"additional","affiliation":[{"name":"Research Unit n\u00b0UMR1341 NuMeCan\u2013Nutrition, M\u00e9tabolismes et Cancer, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"},{"name":"Department of Liver Diseases CHU de Rennes, Rennes 1 University, Pontchaillou Hospital, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olivier","family":"Lor\u00e9al","sequence":"additional","affiliation":[{"name":"Research Unit n\u00b0UMR1341 NuMeCan\u2013Nutrition, M\u00e9tabolismes et Cancer, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julien","family":"Calderaro","sequence":"additional","affiliation":[{"name":"Assistance Publique-H\u00f4pitaux de Paris, Department of Pathology Henri Mondor, 94000 Cr\u00e9teil, France"},{"name":"INSERM U955, Team Pathophysiology and Therapy of Chronic Viral Hepatitis and Related Cancers, 94000 Cr\u00e9teil, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zine-Eddine","family":"Khene","sequence":"additional","affiliation":[{"name":"Impact TEAM, Laboratoire Traitement du Signal et de l\u2019Image (LTSI) INSERM, Rennes 1 University, Pontchaillou Hospital, 35033 Rennes, France"},{"name":"Department of Urology, CHU de Rennes, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oscar","family":"Acosta","sequence":"additional","affiliation":[{"name":"Impact TEAM, Laboratoire Traitement du Signal et de l\u2019Image (LTSI) INSERM, Rennes 1 University, Pontchaillou Hospital, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renaud","family":"De Crevoisier","sequence":"additional","affiliation":[{"name":"Impact TEAM, Laboratoire Traitement du Signal et de l\u2019Image (LTSI) INSERM, Rennes 1 University, Pontchaillou Hospital, 35033 Rennes, France"},{"name":"Department of Radiotherapy, Centre Eug\u00e8ne Marquis, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathalie","family":"Rioux-Leclercq","sequence":"additional","affiliation":[{"name":"Department of Pathology CHU de Rennes, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0772-9753","authenticated-orcid":false,"given":"Thierry","family":"Pecot","sequence":"additional","affiliation":[{"name":"Biosit Platform UAR 3480 CNRS US18 INSERM U955, Rennes 1 University, Pontchaillou Hospital, 35033 Rennes, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sol\u00e8ne-Florence","family":"Kammerer-Jacquet","sequence":"additional","affiliation":[{"name":"Department of Pathology CHU de Rennes, Rennes 1 University, Pontchaillou Hospital, 2 rue Henri Le Guilloux, CEDEX 09, 35033 Rennes, France"},{"name":"Impact TEAM, Laboratoire Traitement du Signal et de 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