.... Preoperative retrospective CT-imaging data were analyzed, and radiomic features were extracted from tumor lesions and renal parenchyma. Machine learning models were trained to predict postoperative new-onset CKD based on clinical information and radiomics. Model performance was assessed using five-fold cross...

... Lu-177 PSMA treatment using machine learning with texture analysis data obtained from pretreatment Gallium-68 (Ga-68) PSMA positron emission tomography/computed tomography (PET/CT). Methods: Eighty-three progressed, and 91 nonprogressed malignant foci on pretreatment Ga-68 PSMA PET/CT of 9 patients...

...) for prediction of surgical complexity. Methods: Fifty-six patients who underwent renal tumor surgery were included. Radiomic features were extracted from contrast-enhanced CT. Machine learning models using radiomic features, the Mayo Adhesive Probability (MAP) score, and/or clinical variables (age, sex, and body...