{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T21:33:13Z","timestamp":1792099993660,"version":"4.4.0"},"reference-count":29,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T00:00:00Z","timestamp":1734480000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T00:00:00Z","timestamp":1734480000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Liver International"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Aims<\/jats:title>\n                    <jats:p>This study aims to develop and validate a machine learning (ML) model predicting hepatocellular carcinoma (HCC) in chronic hepatitis B (CHB) patients after the first 5\u2009years of entecavir (ETV) or tenofovir (TFV) therapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>CHB patients treated with ETV\/TFV for &gt;\u20095\u2009years and not diagnosed with HCC during the first 5\u2009years of therapy were selected from two hospitals. We used 36 variables, including baseline characteristics (age, sex, cirrhosis, and type of antiviral agent) and laboratory values (at baseline, at 5\u2009years, and changes between 5\u2009years) for model development. Five machine learning algorithms were applied to the training dataset and internally validated using a test dataset. External validation was performed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In years 5\u201315, a total of 279\/5908 (4.7%) and 25\/562 (4.5%) patients developed HCC in the derivation and external validation cohorts, respectively. In the training dataset (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20094726), logistic regression showed the highest area under the receiver operating curve (AUC) of 0.803 and a balanced accuracy of 0.735, outperforming other ML algorithms. An ensemble model combining logistic regression and random forest performed best (AUC, 0.811 and balanced accuracy, 0.754). The results from the test dataset (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091182) verified the good performance of the ensemble model (AUC, 0.784 and balanced accuracy, 0.712). External validation confirmed the predictive accuracy of our ensemble model (AUC, 0.862 and balanced accuracy, 0.771). A web\u2010based calculator was developed (\n                      <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/ai-wm.khu.ac.kr\/HCC\/\">http:\/\/ai\u2010wm.khu.ac.kr\/HCC\/<\/jats:ext-link>\n                      ).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The proposed ML model excellently predicted HCC risk beyond year 5 of ETV\/TFV therapy and, therefore, could facilitate individualised HCC surveillance based on risk stratification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/liv.16139","type":"journal-article","created":{"date-parts":[[2024,12,18]],"date-time":"2024-12-18T07:35:16Z","timestamp":1734507316000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Machine Learning Model to Predict De Novo Hepatocellular Carcinoma Beyond Year 5 of Antiviral Therapy in Patients With Chronic Hepatitis B"],"prefix":"10.1111","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3594-3688","authenticated-orcid":false,"given":"Yeonjung","family":"Ha","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, CHA Bundang Medical Center CHA University  Seongnam\u2010si Gyeonggi\u2010do South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seungseok","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, College of Electronics and Informatics Kyung Hee University  Yongin\u2010si Gyeonggi\u2010do South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1878-0215","authenticated-orcid":false,"given":"Jihye","family":"Lim","sequence":"additional","affiliation":[{"name":"Division of Gastroenterology and Hepatology, Department of Internal Medicine, College of Medicine The Catholic University of Korea  Seoul South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwanjoo","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, CHA Bundang Medical Center CHA University  Seongnam\u2010si Gyeonggi\u2010do South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young Eun","family":"Chon","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, CHA Bundang Medical Center CHA University  Seongnam\u2010si Gyeonggi\u2010do South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joo Ho","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, CHA Bundang Medical Center CHA University  Seongnam\u2010si Gyeonggi\u2010do South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kwan Sik","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, CHA Bundang Medical Center CHA University  Seongnam\u2010si Gyeonggi\u2010do South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3180-3178","authenticated-orcid":false,"given":"Kang Mo","family":"Kim","sequence":"additional","affiliation":[{"name":"Asan Liver Center, Asan Medical Center University of Ulsan College of Medicine  Seoul South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7336-1371","authenticated-orcid":false,"given":"Ju Hyun","family":"Shim","sequence":"additional","affiliation":[{"name":"Asan Liver Center, Asan Medical Center University of Ulsan College of Medicine  Seoul South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danbi","family":"Lee","sequence":"additional","affiliation":[{"name":"Asan Liver Center, Asan Medical Center University of Ulsan College of Medicine  Seoul South 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