This targeted resource is aimed at increasing understanding of this often asymptomatic, progressive eye disease, particularly in developing countries. Healthcare professionals, students, and policymakers will find this resource valuable with its straightforward, easy to understand, curriculum-aligned content. Its emphasis on practical applications and awareness-building make it a valuable tool for advancing glaucoma care and fostering interdisciplinary collaboration in eye health.
Table of Contents
1. Introduction to Glaucoma: Epidemiology and the Transformative Role of AI in Screening and Early Diagnosis2. Anatomy and Physiology of the Eye: Enhancing Understanding Through AI-Driven Modeling
3. Evaluating the Impact of Current Glaucoma Medications on Ocular Surface: AI-Assisted Monitoring and Optimization
4. AI-Enabled Monitoring of Glaucoma Progression: Innovations in Tracking Disease Dynamics
5. AI-Driven Diagnosis and Care Strategies for Glaucoma Patients in Developing Countries
6. Genetics, Types, and Risk Factors of Glaucoma: Insights Gained Through AI and Machine Learning
7. Advanced Glaucoma Imaging Techniques: Classification and Analysis Using AI Algorithms
8. The Role of AI and Machine Learning in Revolutionizing Glaucoma Diagnosis and Management
9. Assessing the Accuracy of AI and ML in Glaucoma Screening and Clinical Practice
10. Future Perspectives: Leveraging AI to Make Glaucoma Diagnosis More Accessible and Effective in Developing Countries
Authors
Mohammad Sufian Badar Senior Teaching Faculty, Department of Bioengineering, University of California, Riverside, CA, USA.Mohammad Sufian Badar, PhD, is an Assistant Professor in the Department of Computer Science and Engineering, SEST, Jamia Hamdard, New Delhi. Previously, he was a Senior Teaching Faculty at UC Riverside, CA, USA, and an Analytics Architect at CenturyLink in Denver, CO, USA. He holds an MS in Molecular Science and Nanotechnology and a PhD in Engineering from Louisiana Tech University. He earned an MSc in Bioinformatics from Jamia Millia Islamia, New Delhi. With many years of teaching, research, and industry experience, Dr. Badar has published in conferences and journals, authored chapters on AI, machine learning, blockchain, IoT, and computational biology and has edited and authored several books in his area of interest like AI, ML, computational biology, and the integration of AI/ ML with health sciences.
