{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T05:50:10Z","timestamp":1790315410542,"version":"4.1.0"},"reference-count":37,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Aliment Pharmacol Ther"],"published-print":{"date-parts":[[2024,3]]},"abstract":"<jats:title>Summary<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>The precise estimation of cases with significant fibrosis (SF) is an unmet goal in non\u2010alcoholic fatty liver disease (NAFLD\/MASLD).<\/jats:p><\/jats:sec><jats:sec><jats:title>Aims<\/jats:title><jats:p>We evaluated the performance of machine learning (ML) and non\u2010patented scores for ruling out SF among NAFLD\/MASLD patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Twenty\u2010one ML models were trained (<jats:italic>N<\/jats:italic>\u2009=\u20091153), tested (<jats:italic>N<\/jats:italic>\u2009=\u2009283), and validated (<jats:italic>N<\/jats:italic>\u2009=\u2009220) on clinical and biochemical parameters of histologically\u2010proven NAFLD\/MASLD patients (<jats:italic>N<\/jats:italic>\u2009=\u20091656) collected across 14 centres in 8 Asian countries. Their performance for detecting histological\u2010SF (\u2265F2fibrosis) were evaluated with APRI, FIB4, NFS, BARD, and SAFE (NPV\/F1\u2010score as model\u2010selection criteria).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Patients aged 47\u2009years (median), 54.6% males, 73.7% with metabolic syndrome, and 32.9% with histological\u2010SF were included in the study. Patients with SFvs.no\u2010SF had higher age, aminotransferases, fasting plasma glucose, metabolic syndrome, uncontrolled diabetes, and NAFLD activity score (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001, each). ML models showed 7%\u201312% better discrimination than FIB\u20104 to detect SF. Optimised random forest (RF) yielded best NPV\/F1 in overall set (0.947\/0.754), test set (0.798\/0.588) and validation set (0.852\/0.559), as compared to FIB4 in overall set (0.744\/0.499), test set (0.722\/0.456), and validation set (0.806\/0.507). Compared to FIB\u20104, RF could pick 10 times more patients with SF, reduce unnecessary referrals by 28%, and prevent missed referrals by 78%. Age, AST, ALT fasting plasma glucose, and platelet count were top features determining the SF. Sequential use of SAFE\u2009&lt;\u2009140 and FIB4\u2009&lt;\u20091.2 (when SAFE\u2009&gt;\u2009140) was next best in ruling out SF (NPV of 0.757, 0.724 and 0.827 in overall, test and validation set).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>ML with clinical, anthropometric data and simple blood investigations perform better than FIB\u20104 for ruling out SF in biopsy\u2010proven Asian NAFLD\/MASLD patients.<\/jats:p><\/jats:sec>","DOI":"10.1111\/apt.17891","type":"journal-article","created":{"date-parts":[[2024,2,2]],"date-time":"2024-02-02T06:12:20Z","timestamp":1706854340000},"page":"774-788","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Machine learning improves the prediction of significant fibrosis in Asian patients with metabolic dysfunction\u2010associated steatotic liver disease <scp>\u2013<\/scp> The Gut and Obesity in Asia (GO\u2010ASIA) Study"],"prefix":"10.1111","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4328-0914","authenticated-orcid":false,"given":"Nipun","family":"Verma","sequence":"first","affiliation":[{"name":"Department of Hepatology Postgraduate Institute of Medical Education and Research  Chandigarh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3590-2664","authenticated-orcid":false,"given":"Ajay","family":"Duseja","sequence":"additional","affiliation":[{"name":"Department of Hepatology Postgraduate Institute of Medical Education and Research  Chandigarh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manu","family":"Mehta","sequence":"additional","affiliation":[{"name":"Department of Hepatology Postgraduate Institute of Medical Education and Research  Chandigarh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8567-1676","authenticated-orcid":false,"given":"Arka","family":"De","sequence":"additional","affiliation":[{"name":"Department of Hepatology Postgraduate Institute of Medical Education and Research  Chandigarh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huapeng","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Medicine and Therapeutics The Chinese University of Hong Kong  Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2215-9410","authenticated-orcid":false,"given":"Vincent Wai\u2010Sun","family":"Wong","sequence":"additional","affiliation":[{"name":"Department of Medicine and Therapeutics The Chinese University of Hong Kong  Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grace Lai\u2010Hung","family":"Wong","sequence":"additional","affiliation":[{"name":"Department of Medicine and Therapeutics The Chinese University of Hong Kong  Hong Kong China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruveena Bhavani","family":"Rajaram","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology Unit, Department of Medicine, Faculty of Medicine University of Malaya Medical Centre  Kuala Lumpur Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wah\u2010Kheong","family":"Chan","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology Unit, Department of Medicine, Faculty of Medicine University of Malaya Medical Centre  Kuala Lumpur Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5824-0590","authenticated-orcid":false,"given":"Sanjiv","family":"Mahadeva","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology 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