This is an archive of papers published by the staff and faculty of Fox Chase Cancer Center. For questions about content, please contact Talbot Research Library
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Kidney cancer management 3.0: can artificial intelligence make us better?
Curr Opin Urol. 2021 Apr 20;31(4) :409-415
PMID: 33882560 URL: https://www.ncbi.nlm.nih.gov/pubmed/33882560
AbstractPURPOSE OF REVIEW: Artificial intelligence holds tremendous potential for disrupting clinical medicine. Here we review the current role of artificial intelligence in the kidney cancer space. RECENT FINDINGS: Machine learning and deep learning algorithms have been developed using information extracted from radiomic, histopathologic, and genomic datasets of patients with renal masses. SUMMARY: Although artificial intelligence applications in medicine are still in their infancy, they already hold immediate promise to improve accuracy of renal mass characterization, grade, and prognostication. As algorithms become more robust and generalizable, artificial intelligence is poised to significantly disrupt kidney cancer care.
Notes1473-6586 Lee, Matthew Wei, Shuanzeng Anaokar, Jordan Uzzo, Robert Kutikov, Alexander Journal Article United States Curr Opin Urol. 2021 Apr 20. doi: 10.1097/MOU.0000000000000881.