Prediction of Glaucoma Using Convolutional Neural Network

@article{1705161,
      author = {Kavyasri P P, Akalyaa S, Aanandhavarsini M},
      title = {Prediction of Glaucoma Using Convolutional Neural Network},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {7},
      number = {4},
      pages = {429-433},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1705161.pdf},
      abstract = {Glaucoma, a leading cause of irreversible vision loss, poses a significant public health challenge worldwide. Early detection and timely intervention are crucial in managing this disease effectively. This study presents an innovative approach for the prediction of glaucoma using Convolutional Neural Networks (CNNs), a deep learning technique well-suited for image analysis tasks. This paper contributes to the development of non-invasive, cost-effective, and scalable tools for early glaucoma detection, enabling healthcare professionals to identify at-risk patients and initiate appropriate interventions promptly. The integration of deep learning techniques, particularly CNNs, showcases the potential for artificial intelligence in improving the diagnosis and management of glaucoma, ultimately preserving precious vision and enhancing the quality of life for affected individuals.},
      keywords = {Glaucoma, Deep Learning, Retinal     Images, Early Detection},
      month = {October},
  }