Deep Learning and Glaucoma Specialists

Glaucoma-Deep: Detection of Glaucoma Eye Disease on Retinal Fundus Images using Deep Learning

Detection of glaucoma eye disease is still a challenging task for computer-aided diagnostics (CADx) systems. During eye screening process, the ophthalmologists measures the glaucoma by structure changes in optic disc (OD), loss of nerve fibres (LNF) and atrophy of the peripapillary region (APR). In retinal images, the automated CADx systems are developed to assess this eye disease through segme...

Glaucoma Medication Preferences among Glaucoma Specialists in Mexico

Aim To determine the glaucoma specialists' preferences for the different brands of topical glaucoma medications available in Mexico. Materials and methods A web-based survey was sent to 150 board-certified glaucoma specialists in Mexico, with 14 questions related to brand preferences for all glaucoma medications available in Mexico. Participants were asked to select each glaucoma medication c...

Specialists in Identifying Learning Disabled

Individuals who are learning disabled possess average to above average intelligence but have difficulty acquiring, storing, and/or retrieving information in certain areas. The primary reason for this difficulty is thus not lack of intelligence-nor is it an emotional block, poor instruction, or a disadvantaged background. Rather, the reason is a deficit, apparently of neurological origin, in one...

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

Bayesian Deep Learning | Uncertainty in Deep Learning