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Machine Learning in Radiomic Renal Mass Characterization: Fundamentals, Applications, Challenges, and Future Directions

Burak Koçak, Ece Ateş Kuş, Aytül Hande Yardımcı, Ceyda Turan Bektaş, Özgür Kılıçkesmez

2020American Journal of Roentgenology19 citationsDOI

Abstract

ML currently has a very low barrier to entry into general medical practice because of the availability of many open-source, free, and easy-to-use toolboxes. Therefore, it should not be surprising to see its related applications in renal mass characterization. A wider picture of the previous works might be beneficial to move this field forward.

Topics & Concepts

MedicineRenal massMedical physicsCharacterization (materials science)Data scienceInternal medicineNanotechnologyKidneyMaterials scienceNephrectomyComputer scienceRenal cell carcinoma treatmentRadiomics and Machine Learning in Medical ImagingMRI in cancer diagnosis
Machine Learning in Radiomic Renal Mass Characterization: Fundamentals, Applications, Challenges, and Future Directions | Litcius