Generative artificial intelligence in oncology.

Journal: Current opinion in urology
PMID: 40026054

Abstract

PURPOSE OF REVIEW: By leveraging models such as large language models (LLMs) and generative computer vision tools, generative artificial intelligence (GAI) is reshaping cancer research and oncologic practice from diagnosis to treatment to follow-up. This timely review provides a comprehensive overview of the current applications and future potential of GAI in oncology, including in urologic malignancies.

Authors

  • Conner Ganjavi
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Sam Melamed
    USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine.
  • Brett Biedermann
    Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Michael B Eppler
    Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Severin Rodler
    Department of Urology, Klinikum der Universitaet Muenchen, Munich, Germany.
  • Ethan Layne
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Francesco Cei
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Inderbir Gill
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Giovanni E Cacciamani
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA - giovanni.cacciamani@med.usc.edu.

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