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Although structural abnormalities in the cerebellum have been demonstrated in schizophrenia, neuroimaging techniques are not yet applicable to identify them given the lack of biomarkers. We aimed to develop a robust diagnostic model for schizophrenia using radiomic features from T1\u2010weighted magnetic resonance imaging (T1\u2010MRI) of the cerebellum.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A total of 336 participants (174 schizophrenia; 162 healthy controls [HCs]) were allocated to training (122 schizophrenia; 115 HCs) and test (52 schizophrenia; 47 HCs) cohorts. We obtained 2568 radiomic features from T1\u2010MRI of the cerebellar subregions. After feature selection, a light gradient boosting machine classifier was trained. The discrimination and calibration of the model were evaluated. SHapley Additive exPlanations (SHAP) was applied to determine model interpretability.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We identified 17 radiomic features to differentiate participants with schizophrenia from HCs. In the test cohort, the radiomics model had an area under the curve, accuracy, sensitivity, and specificity of 0.89 (95% confidence interval: 0.82\u20130.95), 78.8%, 88.5%, and 75.4%, respectively. The model explanation by SHAP suggested that the second\u2010order size zone non\u2010uniformity feature from the right lobule IX and first\u2010order energy feature from the right lobules V and VI were highly associated with the risk of schizophrenia.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The radiomics model focused on the cerebellum demonstrates robustness in diagnosing schizophrenia. Our results suggest that microcircuit disruption in the posterior cerebellum is a disease\u2010defining feature of schizophrenia, and radiomics modeling has potential for supporting biomarker\u2010based decision\u2010making in clinical practice.<\/jats:p><\/jats:sec>","DOI":"10.1111\/pcn.13707","type":"journal-article","created":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T10:54:10Z","timestamp":1719917650000},"page":"527-535","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Identification of schizophrenia by applying interpretable radiomics modeling with structural magnetic resonance imaging of the cerebellum"],"prefix":"10.1111","volume":"78","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1669-4014","authenticated-orcid":false,"given":"Minji","family":"Bang","sequence":"first","affiliation":[{"name":"Department of Psychiatry CHA Bundang Medical Center, CHA University School of Medicine  Seongnam Republic 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