Diagnosis and Analysis of Glaucoma Using Ai and Ml for Medical Imaging

Badar, Mohammad Sufian (Editor)

ISBN 10: 0443449112 / ISBN 13: 9780443449116

Published by Academic Pr, 2026

About this Item

330 pages. 9.25x7.50x9.25 inches. In Stock.

Seller Inventory # __0443449112

Bibliographic Details

• Title: Diagnosis and Analysis of Glaucoma Using Ai and Ml for Medical Imaging
• Publisher: Academic Pr
• Publication Date: 2026
• Language: English
• ISBN 10: 0443449112
• ISBN 13: 9780443449116
• Binding: Paperback
• Condition: Brand New
• Weight: 0.45 kilograms

About this title

Synopsis

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 artificial intelligence (AI) and machine learning (ML) in improving diagnosis and management. Sections explore causes, symptoms, diagnostic challenges, and treatment strategies for glaucoma, integrating insights on how AI and ML 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 makes it a valuable tool for advancing glaucoma care and fostering interdisciplinary collaboration in eye health.

• 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

About the Author

Mohammad Sufian Badar, PhD, is a Professor (temporary) in the Department of Computer Science and Engineering, SEST, Jamia Hamdard, New Delhi, India. Previously, he was Senior Teaching Faculty at UC Riverside, CA, United States, and an Analytics Architect at CenturyLink in Denver, CO, United States. He holds an MS in Molecular Science and Nanotechnology and a PhD in Engineering from Lusiana Tech University. Before that, he earned an MSc. in Bioinformatics from Jamia Millia Islamia, New Delhi. With over 18 years of teaching, research, and industry experience, Dr. Sufian has published in conferences and journals, authored chapters on AI, ML, Blockchain, IoT, Computational Biology, and has six books with Elsevier, Springer, and Bentham. His area of interest is in AI, ML, Computational Biology, and the integration of AI/ML with Health Sciences.