Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences.

Journal: European journal of cancer (Oxford, England : 1990)
PMID: 40107091

Abstract

BACKGROUND: Decisions on the best available treatment in clinical oncology are based on expert opinions in multidisciplinary cancer conferences (MCC). Artificial intelligence (AI) could increase evidence-based treatment by generating additional treatment recommendations (TR). We aimed to develop such an AI system for urothelial carcinoma (UC) and renal cell carcinoma (RCC).

Authors

  • Gregor Duwe
    Department of Urology and Pediatric Urology, University Medical Center, Johannes Gutenberg University, Mainz, Germany.
  • Dominique Mercier
    German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany.
  • Verena Kauth
    Department of Urology and Pediatric Urology, University Medical Center, Johannes Gutenberg University, Mainz, Germany.
  • Kerstin Moench
    Department of Urology and Pediatric Urology, University Medical Center, Johannes Gutenberg University, Mainz, Germany.
  • Vikas Rajashekar
    German Research Center for Artificial Intelligence, Research Unit Smart Data & Knowledge Services, Trippstadter Strasse 122, Kaiserslautern 67663, Germany.
  • Markus Junker
    Research Unit Smart Data and Knowledge Services, German Research Center for Artificial Intelligence, Kaiserslautern, Germany.
  • Andreas Dengel
    German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germnay. Andreas.Dengel@dfki.de.
  • Axel Haferkamp
    Department of Urology and Pediatric Urology, University Medical Center, Johannes Gutenberg University, Mainz, Germany.
  • Thomas Höfner
    Department of Urology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

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