Hybrid attention-based deep learning for multi-label ophthalmic disease detection on fundus images.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Published Date: May 29, 2025

Abstract

BACKGROUND: Ophthalmic diseases significantly impact vision and quality of life. Early diagnosis using fundus images is critical for timely treatment. Traditional deep learning models often lack accuracy, interpretability, and efficiency for multi-label classification tasks in ophthalmology.

Authors

  • Rabiya Hanfi
    Department of Computer Science & Engineering, Rabindranath Tagore University, Bhopal, India. rabiyahanfidr@gmail.com.
  • Harsh Mathur
    Department of Computer Science & Engineering, Rabindranath Tagore University, Bhopal, India.
  • Ritu Shrivastava
    Department of Computer Science & Engineering, Sagar Institute of Research and Technology, Bhopal, India.

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