Computational Methods and Deep Learning for Ophthalmology
Artificial Intelligence and deep learning are transforming modern medicine, and ophthalmology is one of the fields where these innovations are having the greatest impact. Computational Methods and Deep Learning for Ophthalmology is a cutting-edge resource that explores how AI-driven technologies are reshaping the diagnosis, screening, and management of eye diseases. Now available at Books Hub Pk, this book is an essential reference for ophthalmologists, researchers, computer scientists, and postgraduate trainees who want to stay ahead in the era of digital healthcare.
This book brings together leading experts in ophthalmology, biomedical engineering, and artificial intelligence to present a multidisciplinary perspective. It explains the core computational techniques, machine learning models, and deep learning algorithms being applied in ophthalmology, while also highlighting their clinical applications in retinal imaging, glaucoma, diabetic retinopathy, macular degeneration, and corneal diseases.
Key Features of Computational Methods and Deep Learning for Ophthalmology:
Comprehensive overview of AI, machine learning, and deep learning techniques in ophthalmology.
Clinical applications in automated disease detection, image segmentation, and predictive analytics.
Detailed coverage of retinal image analysis, OCT interpretation, and fundus photography using AI.
Insights into cloud-based screening systems, teleophthalmology, and digital health platforms.
Discussion of challenges such as data quality, ethics, bias, and clinical validation.
Future directions of AI-driven ophthalmology and its role in personalized eye care.
