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There were 34, 15 and 28 patients with complications in each cohort. The complications included microvascular complications, infection, diabetic ketosis and hypoglycemia. In PPDM-A patients\u2019 first pancreatitis episode, 2398 radiomics features were extracted from CECT images (arterial and venous phases). FeAture Explorer generated the machine learning pipeline and selected important radiomics features. Gaussian processes classifiers built radiomics and clinical-radiomics models, while Naive Bayes classifiers built the clinical model. The SHAP method was applied to provide insights into the model\u2019s predictive process.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The radiomics model predicted PPDM-A complications with the area under the receiver operating characteristic curve (AUC) of 0.95, 0.888, and 0.948 in training, internal, and external cohorts. In external cohort, the radiomics model significantly outperformed the clinical model (AUC 0.948 vs. 0.713,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.002), while the combined model showed no significant difference from the radiomics model (AUC 0.933 vs. 0.948,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.638). The SHAP technology provided physicians with insights into the global and individual impacts of radiomic features on model predictions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The CECT\u2011based radiomics model showed favorable prognostic performance for the prognosis of PPDM\u2011A. SHAP analysis interpreted the model\u2019s mechanism, enhancing its clinical reliability and transparency.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12880-026-02258-7","type":"journal-article","created":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T02:33:14Z","timestamp":1773369194000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["An interpretable radiomics model based on contrast\u2011enhanced pancreatic computed tomography for predicting the prognosis of post-acute pancreatitis diabetes mellitus"],"prefix":"10.1186","volume":"26","author":[{"given":"Ran","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan-Li","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang-Jing","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yin-Deng","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Di","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi-Gang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Di","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixuan","family":"Song","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,13]]},"reference":[{"key":"2258_CR1","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1080\/17446651.2024.2382958","volume":"19","author":"J Cho","year":"2024","unstructured":"Cho J, Petrov MS. 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Due to the retrospective design, patient informed consent was waived.","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":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"201"}}