A hybrid framework for glaucoma detection through federated machine learning and deep learning models.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: Glaucoma, the second leading cause of global blindness, demands timely detection due to its asymptomatic progression. This paper introduces an advanced computerized system, integrates Machine Learning (ML), convolutional neural networks (CNNs), and image processing for accurate glaucoma detection using medical imaging data, surpassing prior research efforts.

Authors

  • Abeer Aljohani
    Department of Computer Science , Applied College, Taibah University, Medina, 42353, Kingdom of Saudi Arabia. aahjohani@taibahu.edu.sa.
  • Rua Y Aburasain
    Department of Computer Science, College of Engineering and Computer Science, Jazan University, Jazan, 45142, Kingdom of Saudi Arabia.