{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T06:39:58Z","timestamp":1790750398195,"version":"4.1.0"},"reference-count":64,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2023,10,12]],"date-time":"2023-10-12T00:00:00Z","timestamp":1697068800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundaci\u00f3n Investigaci\u00f3n Hospital General Universitario de Valencia"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Metabolic Associated Fatty Liver Disease (MASLD) is a condition that is often present in patients with a history of cholecystectomy. This is because both situations share interconnected metabolic pathways. This study aimed to establish a predictive model that allows for the identification of patients at risk of developing hepatic fibrosis following this surgery, with potential implications for surgical decision-making. A retrospective cross-sectional analysis was conducted in four hospitals using a database of 211 patients with MASLD who underwent cholecystectomy. MASLD diagnosis was established through liver biopsy or FibroScan, and non-invasive test scores were included for analysis. Various Machine Learning (ML) methods were employed, with the Adaptive Boosting (Adaboost) system selected to build the predictive model. Platelet level emerged as the most crucial variable in the predictive model, followed by dyslipidemia and type-2 diabetes mellitus. FIB-4 score proved to be the most reliable non-invasive test. The Adaboost algorithm improved the results compared to the other methods, excelling in both accuracy and area under the curve (AUC). Moreover, this system holds promise for implementation in hospitals as a valuable diagnostic support tool. In conclusion, platelet level (&lt;150,000\/dL), dyslipidemia, and type-2 diabetes mellitus were identified as primary risk factors for liver fibrosis in MASLD patients following cholecystectomy. FIB-4 score is recommended for decision-making, particularly when the indication for surgery is uncertain. This predictive model offers valuable insights into risk stratification and personalized patient management in post-cholecystectomy MASLD cases.<\/jats:p>","DOI":"10.3390\/jcm12206489","type":"journal-article","created":{"date-parts":[[2023,10,12]],"date-time":"2023-10-12T12:46:13Z","timestamp":1697114773000},"page":"6489","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Personalized Risk Assessment of Hepatic Fibrosis after Cholecystectomy in Metabolic-Associated Steatotic Liver Disease: A Machine Learning Approach"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9794-7449","authenticated-orcid":false,"given":"Miguel","family":"Su\u00e1rez","sequence":"first","affiliation":[{"name":"Gastroenterology Department, Virgen de la Luz Hospital, 16002 Cuenca, Spain"},{"name":"Medical Analysis Expert Group, Institute of Technology, Universidad de Castilla-La Mancha, 160071 Cuenca, Spain"},{"name":"Medical Analysis Expert Group, Instituto de Investigaci\u00f3n Sanitaria de Castilla-La Mancha (IDISCAM), 45071 Toledo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raquel","family":"Mart\u00ednez","sequence":"additional","affiliation":[{"name":"Gastroenterology Department, Virgen de la Luz Hospital, 16002 Cuenca, Spain"},{"name":"Medical Analysis Expert Group, Instituto de Investigaci\u00f3n Sanitaria de Castilla-La Mancha (IDISCAM), 45071 Toledo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ana Mar\u00eda","family":"Torres","sequence":"additional","affiliation":[{"name":"Medical Analysis Expert Group, Institute of Technology, Universidad de Castilla-La Mancha, 160071 Cuenca, Spain"},{"name":"Medical Analysis Expert Group, Instituto de Investigaci\u00f3n Sanitaria de Castilla-La Mancha (IDISCAM), 45071 Toledo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonio","family":"Ram\u00f3n","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, General University Hospital, 46014 Valencia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pilar","family":"Blasco","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, General University Hospital, 46014 Valencia, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jorge","family":"Mateo","sequence":"additional","affiliation":[{"name":"Medical Analysis Expert Group, Institute of Technology, Universidad de Castilla-La Mancha, 160071 Cuenca, Spain"},{"name":"Medical Analysis Expert Group, Instituto de Investigaci\u00f3n Sanitaria de Castilla-La Mancha (IDISCAM), 45071 Toledo, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Rinella, M.E., Lazarus, J.V., Ratziu, V., Francque, S.M., Sanyal, A.J., Kanwal, F., Romero, D., Abdelmalek, M.F., Anstee, Q.M., and Arab, J.P. 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