Artificial Intelligence in Kidney Cancer.

Journal: American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Published Date:

Abstract

Artificial intelligence is rapidly expanding into nearly all facets of life, particularly within the field of medicine. The diagnosis, characterization, management, and treatment of kidney cancer is ripe with areas for improvement that may be met with the promises of artificial intelligence. Here, we explore the impact of current research work in artificial intelligence for clinicians caring for patients with renal cancer, with a focus on the perspectives of radiologists, pathologists, and urologists. Promising preliminary results indicate that artificial intelligence may assist in the diagnosis and risk stratification of newly discovered renal masses and help guide the clinical treatment of patients with kidney cancer. However, much of the work in this field is still in its early stages, limited in its broader applicability, and hampered by small datasets, the varied appearance and presentation of kidney cancers, and the intrinsic limitations of the rigidly structured tasks artificial intelligence algorithms are trained to complete. Nonetheless, the continued exploration of artificial intelligence holds promise toward improving the clinical care of patients with kidney cancer.

Authors

  • Robert Rasmussen
    Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX.
  • Thomas Sanford
    Molecular Imaging Program, National Cancer Institute, NIH, Bethesda, MD, USA.
  • Anil V Parwani
    Department of Pathology, The Ohio State University Wexner Medical Centre, Columbus, OH, USA.
  • Iván Pedrosa
    Chief of MRI. Professor of Radiology, Urology, Advanced Imaging Research Center and Biomedical Engineering. University of Texas Southwestern Medical Center, Dallas, TX, United States. Electronic address: ivan.pedrosa@utsouthwestern.edu.