Artificial intelligence (AI) is the integration of human tasks into machine processes. The role of AI in kidney cancer evaluation, management, and outcome predictions are constantly evolving. We performed a narrative review utilizing PubMed electronic database to query AI as a method of analysis in kidney cancer research.
Key search-words included: Artificial Intelligence, Supervised/Unsupervised Machine Learning, Deep Learning, Natural Language Processing, Neural Networks, radiomics, pathomics, and kidney or renal neoplasms or cancer. 72 clinically relevant and impactful studies related to imaging, histopathology, and outcomes were recognized. We anticipate the incorporation of AI tools into future clinical decision-making for kidney cancer.
Urology. 2024 Jul 17 [Epub ahead of print]
Adri M Durant, Ramon Correa Medero, Logan Briggs, Mouneeb Choudry, Mimi Nguyen, Aneeta Channar, Umar Ghaffar, Imon Banerjee, Irbaz Bin Riaz, Haidar Abdul-Muhsin
Department of Urology, Mayo Clinic Arizona, Phoenix, AZ, USA. Electronic address: ., School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA., Department of Urology, Mayo Clinic Arizona, Phoenix, AZ, USA., Division of Hematology and Oncology, Department of Internal Medicine, Mayo Clinic Arizona, Phoenix, AZ, USA., Department of Urology, Mayo Clinic Rochester, Rochester, MN, USA., School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, USA; Department of Radiology, Mayo Clinic Arizona, Scottsdale, AZ, USA.
PubMed http://www.ncbi.nlm.nih.gov/pubmed/39029807