Bayesian and deep-learning models applied to the early detection of ovarian cancer using multiple longitudinal biomarkers.

Journal: Cancer medicine
Published Date: Apr 1, 2024

Abstract

BACKGROUND: Ovarian cancer is the most lethal of all gynecological cancers. Cancer Antigen 125 (CA125) is the best-performing ovarian cancer biomarker which however is still not effective as a screening test in the general population. Recent literature reports additional biomarkers with the potential to improve on CA125 for early detection when using longitudinal multimarker models.

Authors

  • Luis Abrego
    Department of Women's Cancer, EGA Institute for Women's Health, University College London, London, UK.
  • Alexey Zaikin
    Department of Mathematics, University College London, London, UK; Institute for Women's Health, University College London, London, UK; Lobachevsky State University of Nizhniy Novgorod, Nizhniy Novgorod, Russia.
  • Ines P Marino
    Department of Biology and Geology, Physics and Inorganic Chemistry, Universidad Rey Juan Carlos, Madrid, Spain.
  • Mikhail I Krivonosov
    Research Center for Trusted Artificial Intelligence, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow, Russia.
  • Ian Jacobs
    Department of Women's Cancer, EGA Institute for Women's Health, University College London, London, UK.
  • Usha Menon
    Department of Women's Cancer, UCL Elizabeth Garrett Anderson Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, London, WC1E 6AU, UK.
  • Aleksandra Gentry-Maharaj
    Department of Women's Cancer, EGA Institute for Women's Health, University College London, London, UK.
  • Oleg Blyuss
    Institute for Women's Health, University College London, London, UK.

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