Mortality Prediction of Patients with Subarachnoid Hemorrhage Using a Deep Learning Model Based on an Initial Brain CT Scan.

Journal: Brain sciences
Published Date: Dec 22, 2023

Abstract

BACKGROUND: Subarachnoid hemorrhage (SAH) entails high morbidity and mortality rates. Convolutional neural networks (CNN) are capable of generating highly accurate predictions from imaging data. Our objective was to predict mortality in SAH patients by processing initial CT scans using a CNN-based algorithm.

Authors

  • Sergio García-García
    Neurosurgery Department, Rio Hortega University Hospital, 47012 Valladolid, Spain.
  • Santiago Cepeda
    Neurosurgery Department, Rio Hortega University Hospital, 47012 Valladolid, Spain.
  • Dominik Müller
    IT-Infrastructure for Translational Medical Research, University of Augsburg, 86159 Augsburg, Germany.
  • Alejandra Mosteiro
    Neurosurgery Department, Hospital Clinic de Barcelona, 08036 Barcelona, Spain.
  • Ramón Torné
    Neurosurgery Department, Hospital Clinic de Barcelona, 08036 Barcelona, Spain.
  • Silvia Agudo
    Neurosurgery Department, Rio Hortega University Hospital, 47012 Valladolid, Spain.
  • Natalia de la Torre
    Neurosurgery Department, Rio Hortega University Hospital, 47012 Valladolid, Spain.
  • Ignacio Arrese
    Neurosurgery Department, Rio Hortega University Hospital, 47012 Valladolid, Spain.
  • Rosario Sarabia
    Neurosurgery Department, Rio Hortega University Hospital, 47012 Valladolid, Spain.

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