UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.

Journal: World journal of urology
Published Date: Jun 4, 2025

Abstract

PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcinoma (RCC) is a cornerstone of presurgical planning. We sought to create and validate U.N.I.K., a machine learning (ML) model capable of predicting benign lesions on final histological report.

Authors

  • Cesare Saitta
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Giuseppe Garofano
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Giacomo Musso
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Hajime Tanaka
    Departments of 1Urology and.
  • Dattatraya Patil
    Department of Urology, Emory Medical Center, Atlanta, USA.
  • Vi Nguyen
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: vnguyen31@bwh.harvard.edu.
  • Kit L Yuen
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Benjamin Baker
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Mai Dabbas
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Margaret F Meagher
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Dhruv Puri
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Natalie Birouty
    Department of Urology, UC San Diego Health System, San Diego, USA.
  • Omer Baker
    Kay Durairaj, MD, A Medical Corp, Pasadena, California, USA.
  • Masaki Kobayashi
    Mathematical Science Center, University of Yamanashi, Takeda 4-3-11, Kofu, Yamanashi 400-8511, Japan.
  • Shohei Fukuda
    Department of Urology, Tokyo Medical and Dental University, Tokyo, Japan.
  • Marco Paciotti
    Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium; ORSI Academy, Ghent, Belgium; Department of Urology, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy.
  • Giovanni Lughezzani
    Humanitas Clinical and Research Center-IRCCS, Department of Urology, Rozzano, Italy.
  • Alessandro Larcher
    Division of Oncology, Unit of Urology, IRCCS Ospedale San Raffaele, Milan, Italy.
  • Umberto Capitanio
    Unit of Urology, Division of Experimental Oncology, Urological Research Institute (URI), IRCCS Ospedale San Raffaele, Milan, Italy.
  • Riccardo Melloni
    Department of Urology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Mario Catanzaro
    Department of Urology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Sebastiano Nazzani
    Department of Urology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Nicola Nicolai
    Department of Urology, IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Yasuhisa Fujii
    Department of Urology, Tokyo Medical and Dental University Graduate School, Tokyo, Japan. y-fujii.uro@tmd.ac.jp.
  • Viraj Master
    Department of Urology, Emory University, Atlanta, Georgia.
  • Nicolomaria Buffi
    Department of Urology, Humanitas Clinical and Research Institute IRCCS, Rozzano, Italy; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.
  • Ithaar H Derweesh
    Department of Urology, UC San Diego School of Medicine, La Jolla, CA, USA. Electronic address: iderweesh@gmail.com.

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