A probabilistic inference algorithm for early detection of age related macular degeneration

Abstract

Age Related Macular Degeneration or ARMD is a retinal disorder that causes blindness over people of older age group. ARMD is associated with age and is a leading cause of blindness around the world. There is no specific medicine to fully cure ARMD but its development can be controlled by regular exercises and a healthy lifestyle if it is detected early. With a rising population of old age group of people, it becomes important to detect ARMD as early as possible in order to contain its development further. This research attempts to develop an algorithm based on probabilistic inference through Bayesian Network by analyzing large datasets collected from previous cases where datasets include elements of risk factors that could cause ARMD along with eye images. Unlike most of the approaches in detecting ARMD this work not only analyses eye images but also includes analysis of various factors causing the disorder. To include the study and analysis of the presence of factors causing ARMD is sensible because those factors are good indicators when the need is an early detection.