{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T06:56:02Z","timestamp":1793861762045,"version":"4.6.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Bureau of Science & Technology and Intellectual Property Nanchong City","award":["20SXQT0303"],"award-info":[{"award-number":["20SXQT0303"]}]},{"name":"Bureau of Science & Technology and Intellectual Property Nanchong City","award":["20SXQT0303"],"award-info":[{"award-number":["20SXQT0303"]}]},{"name":"Bureau of Science & Technology and Intellectual Property Nanchong City","award":["20SXQT0303"],"award-info":[{"award-number":["20SXQT0303"]}]},{"name":"Bureau of Science & Technology and Intellectual Property Nanchong City","award":["20SXQT0303"],"award-info":[{"award-number":["20SXQT0303"]}]},{"name":"Bureau of Science & Technology and Intellectual Property Nanchong City","award":["20SXQT0303"],"award-info":[{"award-number":["20SXQT0303"]}]},{"name":"Bureau of Science & Technology and Intellectual Property Nanchong City","award":["20SXQT0303"],"award-info":[{"award-number":["20SXQT0303"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-86290-7","type":"journal-article","created":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T04:03:52Z","timestamp":1736913832000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus"],"prefix":"10.1038","volume":"15","author":[{"given":"Xiyao","family":"Wan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuting","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohua","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,15]]},"reference":[{"key":"86290_CR1","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1007\/s00535-020-01682-y","volume":"55","author":"SH Bharmal","year":"2020","unstructured":"Bharmal, S. H. et al. Trajectories of glycaemia following acute pancreatitis: A prospective longitudinal cohort study with 24 months follow-up. J. Gastroenterol. 55, 775\u2013788 (2020).","journal-title":"J. Gastroenterol."},{"key":"86290_CR2","doi-asserted-by":"publisher","first-page":"1675","DOI":"10.2337\/dc19-0145","volume":"42","author":"J Cho","year":"2019","unstructured":"Cho, J., Scragg, R., Pandol, S. J., Goodarzi, M. O. & Petrov, M. S. Antidiabetic medications and mortality risk in individuals with pancreatic cancer-related diabetes and postpancreatitis diabetes: A nationwide cohort study. Diabetes Care 42, 1675\u20131683 (2019).","journal-title":"Diabetes Care"},{"key":"86290_CR3","doi-asserted-by":"publisher","first-page":"1486","DOI":"10.2337\/dc17-0542","volume":"40","author":"C Woodmansey","year":"2017","unstructured":"Woodmansey, C. et al. Incidence, demographics, and clinical characteristics of diabetes of the exocrine pancreas (type 3c): A retrospective cohort study. Diabetes Care 40, 1486\u20131493 (2017).","journal-title":"Diabetes Care"},{"key":"86290_CR4","doi-asserted-by":"publisher","first-page":"S17","DOI":"10.2337\/dc22-S002","volume":"45","author":"Classification and Diagnosis of Diabetes","year":"2022","unstructured":"Classification and Diagnosis of Diabetes. Standards of medical care in diabetes-2022. Diabetes Care 45, S17\u2013S38 (2022).","journal-title":"Diabetes Care"},{"key":"86290_CR5","doi-asserted-by":"publisher","first-page":"2267","DOI":"10.21037\/qims-23-1232","volume":"14","author":"R Hu","year":"2024","unstructured":"Hu, R. et al. A radiomics model of contrast-enhanced computed tomography for predicting post-acute pancreatitis diabetes mellitus. Quant. Imaging Med. Surg. 14, 2267\u20132279 (2024).","journal-title":"Quant. Imaging Med. Surg."},{"key":"86290_CR6","doi-asserted-by":"publisher","first-page":"488","DOI":"10.2967\/jnumed.118.222893","volume":"61","author":"ME Mayerhoefer","year":"2020","unstructured":"Mayerhoefer, M. E. et al. Introduction to radiomics. J. Nucl. Med. 61, 488\u2013495 (2020).","journal-title":"J. Nucl. Med."},{"key":"86290_CR7","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2021.710982","volume":"12","author":"F Coppola","year":"2021","unstructured":"Coppola, F. et al. Human, all too human? An all-around appraisal of the \u201cartificial intelligence revolution\u201d in medical imaging. Front. Psychol. 12, 710982 (2021).","journal-title":"Front. Psychol."},{"key":"86290_CR8","first-page":"1039","volume":"110","author":"Z Liu","year":"2024","unstructured":"Liu, Z. et al. Noninvasive prediction of perineural invasion in intrahepatic cholangiocarcinoma by clinicoradiological features and computed tomography radiomics based on interpretable machine learning: A multicenter cohort study. Int. J. Surg. 110, 1039\u20131051 (2024).","journal-title":"Int. J. Surg."},{"key":"86290_CR9","doi-asserted-by":"publisher","first-page":"R137","DOI":"10.1530\/EJE-20-0468","volume":"184","author":"MS Petrov","year":"2021","unstructured":"Petrov, M. S. Diagnosis of endocrine disease: Post-pancreatitis diabetes mellitus: Prime time for secondary disease. Eur. J. Endocrinol. 184, R137\u2013R149 (2021).","journal-title":"Eur. J. Endocrinol."},{"key":"86290_CR10","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1136\/gutjnl-2012-302779","volume":"62","author":"PA Banks","year":"2013","unstructured":"Banks, P. A. et al. Classification of acute pancreatitis\u20132012: Revision of the Atlanta classification and definitions by international consensus. Gut 62, 102\u2013111 (2013).","journal-title":"Gut"},{"key":"86290_CR11","doi-asserted-by":"publisher","first-page":"S20","DOI":"10.2337\/dc24-S002","volume":"47","author":"Diagnosis and Classification of Diabetes","year":"2024","unstructured":"Diagnosis and Classification of Diabetes. Standards of care in diabetes-2024. Diabetes Care 47, S20\u2013S42 (2024).","journal-title":"Diabetes Care"},{"key":"86290_CR12","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1016\/j.pan.2017.06.007","volume":"17","author":"MS Petrov","year":"2017","unstructured":"Petrov, M. S. Diabetes of the exocrine pancreas: American Diabetes Association-compliant lexicon. Pancreatology 17, 523\u2013526 (2017).","journal-title":"Pancreatology"},{"key":"86290_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2021.106584","volume":"214","author":"Y Nohara","year":"2022","unstructured":"Nohara, Y., Matsumoto, K., Soejima, H. & Nakashima, N. Explanation of machine learning models using shapley additive explanation and application for real data in hospital. Comput. Methods Programs Biomed. 214, 106584 (2022).","journal-title":"Comput. Methods Programs Biomed."},{"key":"86290_CR14","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.jad.2022.02.072","volume":"305","author":"M Bang","year":"2022","unstructured":"Bang, M. et al. An interpretable radiomics model for the diagnosis of panic disorder with or without agoraphobia using magnetic resonance imaging. J. Affect. Disord. 305, 47\u201354 (2022).","journal-title":"J. Affect. Disord."},{"key":"86290_CR15","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1186\/s12880-023-01089-0","volume":"23","author":"X Cheng","year":"2023","unstructured":"Cheng, X. et al. Predicting response to CCRT for esophageal squamous carcinoma by a radiomics-clinical SHAP model. BMC Med. Imaging 23, 145 (2023).","journal-title":"BMC Med. Imaging"},{"key":"86290_CR16","doi-asserted-by":"publisher","first-page":"540","DOI":"10.1016\/j.dld.2016.12.010","volume":"49","author":"SA Pendharkar","year":"2017","unstructured":"Pendharkar, S. A., Mathew, J. & Petrov, M. S. Age- and sex-specific prevalence of diabetes associated with diseases of the exocrine pancreas: A population-based study. Dig. Liver Dis. 49, 540\u2013544 (2017).","journal-title":"Dig. Liver Dis."},{"key":"86290_CR17","doi-asserted-by":"publisher","first-page":"4857","DOI":"10.1038\/s41598-023-31947-4","volume":"13","author":"J Zhang","year":"2023","unstructured":"Zhang, J. et al. Machine learning for post-acute pancreatitis diabetes mellitus prediction and personalized treatment recommendations. Sci. Rep. 13, 4857 (2023).","journal-title":"Sci. Rep."},{"key":"86290_CR18","doi-asserted-by":"publisher","first-page":"20230382","DOI":"10.1259\/bjr.20230382","volume":"96","author":"S Zhong","year":"2023","unstructured":"Zhong, S. et al. Developing a CT-based radiomics nomogram for predicting post-acute pancreatitis diabetes mellitus incidence. Br. J. Radiol. 96, 20230382 (2023).","journal-title":"Br. J. Radiol."},{"key":"86290_CR19","doi-asserted-by":"publisher","first-page":"637","DOI":"10.3389\/fphys.2019.00637","volume":"10","author":"M Zhi","year":"2019","unstructured":"Zhi, M. et al. Incidence of new onset diabetes mellitus secondary to acute pancreatitis: A systematic review and meta-analysis. Front. Physiol. 10, 637 (2019).","journal-title":"Front. Physiol."},{"key":"86290_CR20","doi-asserted-by":"publisher","first-page":"1212","DOI":"10.4239\/wjd.v14.i8.1212","volume":"14","author":"M Manrai","year":"2023","unstructured":"Manrai, M. et al. Diabetes mellitus as a consequence of acute severe pancreatitis: Unraveling the mystery. World J. Diabetes 14, 1212\u20131225 (2023).","journal-title":"World J. Diabetes"},{"key":"86290_CR21","doi-asserted-by":"publisher","first-page":"726","DOI":"10.1016\/S0140-6736(20)31310-6","volume":"396","author":"L Boxhoorn","year":"2020","unstructured":"Boxhoorn, L. et al. Acute pancreatitis. Lancet 396, 726\u2013734 (2020).","journal-title":"Lancet"},{"key":"86290_CR22","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1148\/radiol.2020191145","volume":"295","author":"A Zwanenburg","year":"2020","unstructured":"Zwanenburg, A. et al. The image biomarker standardization initiative: Standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295, 328\u2013338 (2020).","journal-title":"Radiology"},{"key":"86290_CR23","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2022.868265","volume":"12","author":"L Rundo","year":"2022","unstructured":"Rundo, L. et al. clinically interpretable radiomics-based prediction of histopathologic response to neoadjuvant chemotherapy in high-grade serous ovarian carcinoma. Front. Oncol. 12, 868265 (2022).","journal-title":"Front. Oncol."},{"key":"86290_CR24","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1016\/S2468-1253(21)00019-4","volume":"6","author":"PA Hart","year":"2021","unstructured":"Hart, P. A. et al. Diabetes following acute pancreatitis. Lancet Gastroenterol. Hepatol. 6, 668\u2013675 (2021).","journal-title":"Lancet Gastroenterol. Hepatol."},{"key":"86290_CR25","doi-asserted-by":"publisher","first-page":"3260","DOI":"10.3748\/wjg.v26.i23.3260","volume":"26","author":"BJ Yu","year":"2020","unstructured":"Yu, B. J. et al. Pancreatic necrosis and severity are independent risk factors for pancreatic endocrine insufficiency after acute pancreatitis: A long-term follow-up study. World J. Gastroenterol. 26, 3260\u20133270 (2020).","journal-title":"World J. Gastroenterol."},{"key":"86290_CR26","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1186\/s12967-020-02620-5","volume":"18","author":"N Hou","year":"2020","unstructured":"Hou, N. et al. Predicting 30-days mortality for MIMIC-III patients with sepsis-3: A machine learning approach using XGboost. J. Transl. Med. 18, 462 (2020).","journal-title":"J. Transl. Med."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-86290-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-86290-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-86290-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T16:00:38Z","timestamp":1736956838000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-86290-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,15]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["86290"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-86290-7","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,15]]},"assertion":[{"value":"6 October 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 January 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 authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1985"}}