RT Generic
T1 Artificial intelligence for renal cancer: From imaging to histology and beyond
A1 Kowalewski, Karl-Friedrich
A1 Egen, Luisa
A1 Fischetti, Chanel E.
A1 Puliatti, Stefano
A1 Rivas Juan, Gomez
A1 Taratkin, Mark
A1 Belenchon Ines, Rivero
A1 Abate, Marie Angela Sidoti
A1 Muehlbauer, Julia
A1 Wessels, Frederik
A1 Checcucci, Enrico
A1 Cacciamani, Giovanni
A1 YAU, 
K1 Kidney cancer
K1 Imaging
K1 Technology
K1 Artificial intelligence
K1 Machine learning
K1 Cell carcinoma
K1 Active surveillance
K1 Pulsatile motion
K1 Performance
K1 Validation
K1 Masses
K1 Tumor
K1 Radiomics
K1 Predict
K1 Ct
AB Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging. This creates considerable challenges as approximately 10%-17% of kidney tumors are designated as benign in histopathological evaluation; however, certain co-morbid populations (the obese and elderly) have an increased peri-interventional risk. AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions. The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC. Currently, AI applications can be found in any aspect of RCC management including diagnostics, perioperative care, pathology, and follow-up. Most commonly applied models include neural networks, random forest, support vector machines, and regression. However, for implementation in daily practice, health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets, define meaningful endpoints, and unify interpretation. (C) 2022 Editorial Office of Asian Journal of Urology. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
PB Elsevier singapore pte ltd
SN 2214-3882
YR 2022
FD 2022-07-01
LK http://hdl.handle.net/10668/21881
UL http://hdl.handle.net/10668/21881
LA en
DS RISalud
RD Apr 7, 2025