{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T10:30:12Z","timestamp":1766572212506,"version":"3.48.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T00:00:00Z","timestamp":1766534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T00:00:00Z","timestamp":1766534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["No.8220030273"],"award-info":[{"award-number":["No.8220030273"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Gastroenterol"],"DOI":"10.1186\/s12876-025-04442-5","type":"journal-article","created":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T10:27:10Z","timestamp":1766572030000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ChatGPT improves usability, effectiveness, scalability, interpretability and accessibility, in early diagnosis of metabolic dysfunction-associated fatty liver disease"],"prefix":"10.1186","volume":"25","author":[{"given":"Xiaoying","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhipeng","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahui","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengfu","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhe","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miaomiao","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chaohui","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,24]]},"reference":[{"issue":"9","key":"4442_CR1","doi-asserted-by":"publisher","first-page":"851","DOI":"10.1016\/S2468-1253(22)00165-0","volume":"7","author":"K Riazi","year":"2022","unstructured":"Riazi K, Azhari H, Charette JH, Underwood FE, King JA, Afshar EE, et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol. 2022;7(9):851\u201361.","journal-title":"Lancet Gastroenterol Hepatol"},{"issue":"5","key":"4442_CR2","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1097\/HEP.0000000000000323","volume":"77","author":"ME Rinella","year":"2023","unstructured":"Rinella ME, Neuschwander-Tetri BA, Siddiqui MS, Abdelmalek MF, Caldwell S, Barb D, et al. AASLD practice guidance on the clinical assessment and management of nonalcoholic fatty liver disease. Hepatology. 2023;77(5):1797\u2013835.","journal-title":"Hepatology"},{"issue":"3","key":"4442_CR3","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1136\/gutjnl-2023-331003","volume":"73","author":"HH Lee","year":"2024","unstructured":"Lee HH, Lee HA, Kim EJ, Kim HY, Kim HC, Ahn SH, et al. Metabolic dysfunction-associated steatotic liver disease and risk of cardiovascular disease. Gut. 2024;73(3):533\u201340.","journal-title":"Gut"},{"issue":"1","key":"4442_CR4","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.jhep.2020.03.039","volume":"73","author":"M Eslam","year":"2020","unstructured":"Eslam M, Newsome PN, Sarin SK, Anstee QM, Targher G, Romero-Gomez M, et al. A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol. 2020;73(1):202\u20139.","journal-title":"J Hepatol"},{"issue":"7","key":"4442_CR5","doi-asserted-by":"publisher","first-page":"1999","DOI":"10.1053\/j.gastro.2019.11.312","volume":"158","author":"M Eslam","year":"2020","unstructured":"Eslam M, Sanyal AJ, George J. MAFLD: a consensus-driven proposed nomenclature for metabolic associated fatty liver disease. Gastroenterology. 2020;158(7):1999-e20141.","journal-title":"Gastroenterology"},{"issue":"1","key":"4442_CR6","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1053\/j.gastro.2019.08.058","volume":"158","author":"C Le Berre","year":"2020","unstructured":"Le Berre C, Sandborn WJ, Aridhi S, Devignes MD, Fournier L, Sma\u00efl-Tabbone M, et al. Application of artificial intelligence to gastroenterology and hepatology. Gastroenterology. 2020;158(1):76\u2013e942.","journal-title":"Gastroenterology"},{"issue":"Suppl","key":"4442_CR7","doi-asserted-by":"publisher","first-page":"S171","DOI":"10.3350\/cmh.2022.0426","volume":"29","author":"TC Yip","year":"2023","unstructured":"Yip TC, Lyu F, Lin H, Li G, Yuen PC, Wong VW, et al. Non-invasive biomarkers for liver inflammation in non-alcoholic fatty liver disease: present and future. Clin Mol Hepatol. 2023;29(Suppl):S171\u201383.","journal-title":"Clin Mol Hepatol"},{"issue":"3","key":"4442_CR8","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1016\/j.jhep.2021.05.025","volume":"75","author":"Liver EAftSot","year":"2021","unstructured":"Liver EAftSot. EASL clinical practice guidelines on non-invasive tests for evaluation of liver disease severity and prognosis \u2013\u20092021 update. J Hepatol. 2021;75(3):659\u201389.","journal-title":"J Hepatol"},{"key":"4442_CR9","doi-asserted-by":"publisher","DOI":"10.1038\/srep16494","volume":"5","author":"J Wang","year":"2015","unstructured":"Wang J, Xu C, Xun Y, Lu Z, Shi J, Yu C, et al. ZJU index: a novel model for predicting nonalcoholic fatty liver disease in a Chinese population. Sci Rep. 2015;5:16494.","journal-title":"Sci Rep"},{"issue":"3","key":"4442_CR10","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.jacc.2020.11.030","volume":"77","author":"G Quer","year":"2021","unstructured":"Quer G, Arnaout R, Henne M, Arnaout R. Machine learning and the future of cardiovascular care: JACC state-of-the-art review. J Am Coll Cardiol. 2021;77(3):300\u201313.","journal-title":"J Am Coll Cardiol"},{"issue":"4","key":"4442_CR11","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1038\/s41579-023-00984-1","volume":"22","author":"F Asnicar","year":"2024","unstructured":"Asnicar F, Thomas AM, Passerini A, Waldron L, Segata N. Machine learning for microbiologists. Nat Rev Microbiol. 2024;22(4):191\u2013205.","journal-title":"Nat Rev Microbiol"},{"key":"4442_CR12","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/4304376","volume":"2018","author":"H Ma","year":"2018","unstructured":"Ma H, Xu CF, Shen Z, Yu CH, Li YM. Application of machine learning techniques for clinical predictive modeling: a cross-sectional study on nonalcoholic fatty liver disease in China. BioMed Res Int. 2018;2018:4304376.","journal-title":"BioMed Res Int"},{"key":"4442_CR13","first-page":"27730","volume":"35","author":"L Ouyang","year":"2022","unstructured":"Ouyang L, Wu J, Jiang X, Almeida D, Wainwright C, Mishkin P, et al. Training Language models to follow instructions with human feedback. Adv Neural Inf Process Syst. 2022;35:27730\u201344.","journal-title":"Adv Neural Inf Process Syst"},{"key":"4442_CR14","first-page":"1877","volume":"33","author":"T Brown","year":"2020","unstructured":"Brown T, Mann B, Ryder N, Subbiah M, Kaplan JD, Dhariwal P, et al. Language models are few-shot learners. Adv Neural Inf Process Syst. 2020;33:1877\u2013901.","journal-title":"Adv Neural Inf Process Syst"},{"issue":"5","key":"4442_CR15","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1109\/JAS.2023.123618","volume":"10","author":"T Wu","year":"2023","unstructured":"Wu T, He S, Liu J, Sun S, Liu K, Han Q-L, et al. A brief overview of chatgpt: the history, status quo and potential future development. IEEE CAA J Autom Sin. 2023;10(5):1122\u201336.","journal-title":"IEEE CAA J Autom Sin"},{"issue":"2","key":"4442_CR16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000198","volume":"2","author":"TH Kung","year":"2023","unstructured":"Kung TH, Cheatham M, Medenilla A, Sillos C, De Leon L, Elepa\u00f1o C, et al. Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models. PLoS Digit Health. 2023;2(2):e0000198.","journal-title":"PLoS Digit Health"},{"key":"4442_CR17","doi-asserted-by":"crossref","unstructured":"Bommarito J, Bommarito M, Katz DM, Katz J. GPT as knowledge worker: a zero-shot evaluation of (AI) CPA capabilities. ArXiv Preprint arXiv:230104408 [cs.CL]. 2023. https:\/\/arxiv.org\/abs\/2301.04408.","DOI":"10.2139\/ssrn.4322372"},{"issue":"1","key":"4442_CR18","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00464-x","volume":"4","author":"DM Korngiebel","year":"2021","unstructured":"Korngiebel DM, Mooney SD. Considering the possibilities and pitfalls of generative pre-trained transformer 3 (GPT-3) in healthcare delivery. NPJ Digit Med. 2021;4(1):93.","journal-title":"NPJ Digit Med"},{"issue":"5","key":"4442_CR19","first-page":"418","volume":"32","author":"Chinese Society of Hepatology CMA","year":"2024","unstructured":"Chinese Society of Hepatology CMA. [Guidelines for the prevention and treatment of metabolic dysfunction-associated (non-alcoholic) fatty liver disease (Version 2024)]. Zhonghua Gan Zang Bing Za Zhi. 2024;32(5):418\u201334.","journal-title":"Zhonghua Gan Zang Bing Za Zhi"},{"key":"4442_CR20","doi-asserted-by":"publisher","unstructured":"Feng, Sidong & Chen, Chunyang. (2024). Prompting Is All You Need: Automated Android Bug Replay with Large Language Models. 1-13. https:\/\/doi.org\/10.1145\/3597503.3608137.","DOI":"10.1145\/3597503.3608137"},{"issue":"4","key":"4442_CR21","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1159\/000539371","volume":"17","author":"(EASO) EAftSotLEEAftSoDEEAftSoO","year":"2024","unstructured":"(EASO) EAftSotLEEAftSoDEEAftSoO. EASL-EASD-EASO clinical practice guidelines on the management of metabolic Dysfunction-Associated steatotic liver disease (MASLD). Obes Facts. 2024;17(4):374\u2013444.","journal-title":"Obes Facts"},{"issue":"3","key":"4442_CR22","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1007\/s11154-021-09681-x","volume":"23","author":"Y Li","year":"2022","unstructured":"Li Y, Wang X, Zhang J, Zhang S, Jiao J. Applications of artificial intelligence (AI) in researches on non-alcoholic fatty liver disease(NAFLD): a systematic review. Rev Endocr Metab Disord. 2022;23(3):387\u2013400.","journal-title":"Rev Endocr Metab Disord"},{"issue":"1","key":"4442_CR23","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-024-45325-9","volume":"15","author":"H Ying","year":"2024","unstructured":"Ying H, Liu X, Zhang M, Ren Y, Zhen S, Wang X, et al. A multicenter clinical AI system study for detection and diagnosis of focal liver lesions. Nat Commun. 2024;15(1):1131.","journal-title":"Nat Commun"},{"issue":"1","key":"4442_CR24","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.infoh.2025.01.001","volume":"2","author":"M Mamun","year":"2025","unstructured":"Mamun M, Chowdhury SH, Hossain MM, Khatun MR, Iqbal S. Explainability enhanced liver disease diagnosis technique using tree selection and stacking ensemble-based random forest model. Informatics and Health. 2025;2(1):17\u201340.","journal-title":"Informatics and Health"},{"key":"4442_CR25","doi-asserted-by":"publisher","DOI":"10.1038\/s41575-025-01108-1","author":"IC Wiest","year":"2025","unstructured":"Wiest IC, Bhat M, Clusmann J, Schneider CV, Jiang X, Kather JN. Large language models for clinical decision support in gastroenterology and hepatology. Nat Rev Gastroenterol Hepatol. 2025. https:\/\/doi.org\/10.1038\/s41575-025-01108-1.","journal-title":"Nat Rev Gastroenterol Hepatol"},{"issue":"2","key":"4442_CR26","doi-asserted-by":"publisher","first-page":"454","DOI":"10.1016\/j.jhep.2021.05.003","volume":"75","author":"Y Nan","year":"2021","unstructured":"Nan Y, An J, Bao J, Chen H, Chen Y, Ding H, et al. The Chinese society of hepatology position statement on the redefinition of fatty liver disease. J Hepatol. 2021;75(2):454\u201361.","journal-title":"J Hepatol"}],"container-title":["BMC Gastroenterology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12876-025-04442-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12876-025-04442-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12876-025-04442-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T10:27:11Z","timestamp":1766572031000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12876-025-04442-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,24]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["4442"],"URL":"https:\/\/doi.org\/10.1186\/s12876-025-04442-5","relation":{},"ISSN":["1471-230X"],"issn-type":[{"value":"1471-230X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,24]]},"assertion":[{"value":"27 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of the First Affiliated Hospital, Zhejiang University School of Medicine (reference number 2024IIT-0371). The need for informed consent was waived by the Ethics Committee because the study involved retrospective data collection without any personally identifiable information.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"There were no conflicts of interest or financial disclosures for all authors.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"868"}}