Gündüz, EmrahAlçin, Ömer FarukKızılay, AhmetPiazza, Cesare2022-04-062022-04-062022Gündüz, E., Alçin, Ö. F., Kızılay, A., & Piazza, C. (2021). Radiomics and deep learning approach to the differential diagnosis of parotid gland tumors. Current Opinion in Otolaryngology & Head and Neck Surgery. 30(2), 107-113.1068-95081531-6998https://hdl.handle.net/20.500.12899/914All studies aimed at the differential diagnosis of benign vs. malignant PGTs or the identification of the commonest PGT subtypes were identified, and five studies were found that focused on deep learning-based differential diagnosis of PGTs. Data sets were created in three of these studies with MRI and in two with computed tomography (CT). Additional seven studies were related to radiomics. Of these, four were on MRI-based radiomics, two on CT-based radiomics, and one compared MRI and CT-based radiomics in the same patients.eninfo:eu-repo/semantics/openAccessArtificial intelligenceDeep learningMachine learningParotid gland tumorsRadiomicsArticle10.1097/MOO.0000000000000782.302107113349079572-s2.0-85125965909Q2WOS:000765490100006Q3