Artificial intelligence model for tumoral clinical decision support systems.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVE: Comparative diagnostic in brain tumor evaluation makes possible to use the available information of a medical center to compare similar cases when a new patient is evaluated. By leveraging Artificial Intelligence models, the proposed system is able of retrieving the most similar cases of brain tumors for a given query. The primary objective is to enhance the diagnostic process by generating more accurate representations of medical images, with a particular focus on patient-specific normal features and pathologies. A key distinction from previous models lies in its ability to produce enriched image descriptors solely from binary information, eliminating the need for costly and difficult to obtain tumor segmentation.

Authors

  • Guillermo Iglesias
    Departamento de Sistemas Informáticos, Escuela Técnica Superior de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, Spain. Electronic address: guillermo.iglesias@upm.es.
  • Edgar Talavera
    Departamento de Sistemas Informáticos, Escuela Técnica Superior de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, Spain. Electronic address: e.talavera@upm.es.
  • Jesús Troya
    Infanta Leonor University Hospital. Madrid., Spain.
  • Alberto Díaz-Álvarez
    Departamento de Sistemas Informáticos, Escuela Técnica Superior de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, Spain. Electronic address: alberto.diaz@upm.es.
  • Miguel García-Remesal
    Biomedical Informatics Group, Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Spain. Electronic address: mgremesal@fi.upm.es.