Explainable artificial intelligence to predict and identify prostate cancer tissue by gene expression.

Journal: Computer methods and programs in biomedicine
Published Date: Jul 10, 2023

Abstract

BACKGROUND AND OBJECTIVE: Prostate cancer is one of the most prevalent forms of cancer in men worldwide. Traditional screening strategies such as serum PSA levels, which are not necessarily cancer-specific, or digital rectal exams, which are often inconclusive, are still the screening methods used for the disease. Some studies have focused on identifying biomarkers of the disease but none have been reported for diagnosis in routine clinical practice and few studies have provided tools to assist the pathologist in the decision-making process when analyzing prostate tissue. Therefore, a classifier is proposed to predict the occurrence of PCa that provides physicians with accurate predictions and understandable explanations.

Authors

  • Alberto Ramírez-Mena
    GENYO, Centre for Genomics and Oncological Research: Pfizer -University of Granada - Andalusian Regional Government, Granada, 18016, Spain. Electronic address: alberto.ramirez@genyo.es.
  • Eduardo Andrés-León
    Institute of Parasitology and Biomedicine "López-Neyra" (IPBLN), Spanish National Research Council (CSIC), Granada, 18016, Spain. Electronic address: eduardo.andres@csic.es.
  • Maria Jesus Alvarez-Cubero
    GENYO, Centre for Genomics and Oncological Research: Pfizer -University of Granada - Andalusian Regional Government, Granada, 18016, Spain; Department of Biochemistry and Molecular Biology III and Immunology, University of Granada, Granada, 18071, Spain. Electronic address: mjesusac@ugr.es.
  • Augusto Anguita-Ruiz
    Barcelona Institute for Global Health, ISGlobal, Barcelona, 08003, Spain. Electronic address: augusto.anguita@isglobal.org.
  • Luis Javier Martinez-Gonzalez
    GENYO, Centre for Genomics and Oncological Research: Pfizer -University of Granada - Andalusian Regional Government, Granada, 18016, Spain. Electronic address: luisjavier.martinez@genyo.es.
  • Jesus Alcala-Fdez
    Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, 18071, Spain. Electronic address: jalcala@decsai.ugr.es.

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