Wayne M Getz, Richard Salter, Ludovica Luisa Vissat
Simulation applications to support teaching and research in epidemiological dynamics
BMC medical education
study aim develop validate effectiveness diverse radiomic models distinguishing gnathic fibrous dysplasia fd ossifying fibroma surgery enrolled 220 patients confirmed fd extracted radiomic features nonenhanced ct images following dimensionality reduction feature selection constructed radiomic models using logistic regression support vector machine random forest light gradient boosting machine extreme gradient boosting identified best radiomic model using receiver operating characteristic roc curve analysis combining radiomics features clinical features developed comprehensive model roc curve decision curve analysis dca demonstrated models robustness clinical value extracted 1834 radiomic features ct images reduced eight valuable features achieved high predictive efficiency area curves auc exceeding 095 models ultimately combined model integrates radiomic clinical data displayed superior discriminatory ability auc training cohort 0970 test cohort 0967 dca highlighted optimal clinical efficacy combined model effectively differentiates fd offering noninvasive efficient approach clinical decisionmaking