Deep learning-driven multi-class classification of brain strokes using computed tomography: A step towards enhanced diagnostic precision.

Journal: European journal of radiology
PMID: 40252282

Abstract

OBJECTIVE: To develop and validate deep learning models leveraging CT imaging for the prediction and classification of brain stroke conditions, with the potential to enhance accuracy and support clinical decision-making.

Authors

  • Chathura D Kulathilake
    Department of Radiological Sciences, School of Human Health Sciences, Tokyo Metropolitan University, Japan.
  • Jeevani Udupihille
    Department of Radiology, Faculty of Medicine, University of Peradeniya, Sri Lanka.
  • Sachith P Abeysundara
    Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Sri Lanka.
  • Atsushi Senoo
    Department of Radiological Sciences, School of Human Health Sciences, Tokyo Metropolitan University, Japan. Electronic address: senoo@tmu.ac.jp.

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