Multimodal deep learning for personalized renal cell carcinoma prognosis: Integrating CT imaging and clinical data.

Journal: Computer methods and programs in biomedicine
Published Date: Dec 14, 2023

Abstract

BACKGROUND AND OBJECTIVE: Renal cell carcinoma represents a significant global health challenge with a low survival rate. The aim of this research was to devise a comprehensive deep-learning model capable of predicting survival probabilities in patients with renal cell carcinoma by integrating CT imaging and clinical data and addressing the limitations observed in prior studies. The aim is to facilitate the identification of patients requiring urgent treatment.

Authors

  • Maryamalsadat Mahootiha
    The Intervention Centre, Oslo University Hospital, Oslo, 0372, Norway; Faculty of Medicine, University of Oslo, Oslo, 0372, Norway. Electronic address: marymaho@uio.no.
  • Hemin Ali Qadir
  • Jacob Bergsland
  • Ilangko Balasingham
    Intervention Centre, Oslo University Hospital, Oslo NO-0027, Norway; Institute of Clinical Medicine, University of Oslo, and the Norwegian University of Science and Technology (NTNU), Norway. Electronic address: ilangkob@medisin.uio.no.

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