Related Experiment Video
Updated: Nov 8, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
Kidney cancer management 3.0: can artificial intelligence make us better?
Matthew Lee1, Shuanzeng Wei2, Jordan Anaokar3
1Division of Urologic Oncology.
Purpose 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.
More Related Videos
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
07:13Digital Home-Monitoring of Patients after Kidney Transplantation: The MACCS Platform
Published on: April 12, 2021
Related Concept Videos
Chronic Kidney Disease III: Interprofessional Care
Acute Kidney Injury IV: Diagnostic Studies and Prevention
Chronic Kidney Disease IV: Nursing Management
Chronic Kidney Disease I: Introduction
Kidney Transplant II: Surgical Procedure
Kidney Transplant III: Nursing Management