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Elsevier

Diagnosis and Analysis of Glaucoma using AI and ML for Medical Imaging

  • 1st Edition - July 1, 2026
  • Latest edition
  • Editor: Mohammad Sufian Badar
  • Language: English

Diagnosis and Analysis of Glaucoma using AI and ML for Medical Imaging highlights the importance of early detection while also discussing and updating on current treatment option… Read more

Description

Diagnosis and Analysis of Glaucoma using AI and ML for Medical Imaging highlights the importance of early detection while also discussing and updating on current treatment options to slow disease progression, emphasizing the role of AI and ML in improving diagnosis and management. Sections explore causes, symptoms, diagnostic challenges, and treatment strategies for glaucoma, integrating insights on how artificial intelligence and machine learning models can enhance healthcare delivery. Practical case studies and discussions on how accessible AI tools can be utilized by healthcare workers, NGOs, students, and researchers to address diagnostic barriers prevalent in resource-limited settings are included.

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.

Key features

  • Demonstrates how AI and ML are applied in glaucoma diagnosis and management
  • Employs clear, precise language that makes complex concepts accessible to readers without a computer science background
  • Provides detailed case studies and implementation guidelines, enabling researchers and practitioners to translate theoretical AI techniques into real-world diagnostic tools

Readership

AI researchers, data scientists, and machine learning practitioners interested in applying their skills to healthcare challenges, particularly in medical imaging and ophthalmology

Table of contents

1. Epidemiology of Glaucoma and Role of Glaucoma Screening in Diagnosis
Mohammad Sufian Badar

2.Anatomy and Physiology of Eye
Mohammad Sufian Badar

3.Impact of Current Glaucoma Medication of Ocular Surface
Mohammad Sufian Badar

4. Applications of AI Techniques in Healthcare and Disease Management
Mohammad Sufian Badar

5. Monitoring Glaucoma Progression
Mohammad Sufian Badar

6. Challenges of Glaucoma Diagnosis for Developing Countries
Mohammad Sufian Badar

7. Integrating ML and Optimization Techniques for Improved Disease Prediction
Mohammad Sufian Badar

8. Diagnosis and Care of Glaucoma Patients in Developing Countries
Mohammad Sufian Badar

9. Genetics, Types, and Risk Factors Associated with Glaucoma
Mohammad Sufian Badar

10. Glaucoma Imaging Techniques and Its Classification Using AI
Mohammad Sufian Badar

11. The impact of AI and ML in Glaucoma Diagnosis and Management
Mohammad Sufian Badar

12. Accuracy of Glaucoma Diagnosis by AI and ML in Screening and Clinical
Practice
Budheswar Dehury

13. Necessity of Making Glaucoma Diagnosis More Accessible in Developing Countries
Mohammad “Sufian” Badar

14. Future Prospects: Necessity of Making Glaucoma Diagnosis More Accessible in Developing Countries
Vojč Kocman

Product details

  • Edition: 1
  • Latest edition
  • Published: July 1, 2026
  • Language: English

About the editor

MB

Mohammad Sufian Badar

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.

Affiliations and expertise
Senior Teaching Faculty, Department of Bioengineering, University of California, Riverside, CA, USA