Medical Assistance for Detecting Cataract, Jaundice and Strabismus using Deep Learning

Eye diseases are prevailing either due to poor diet, unhealthy lifestyle, hereditary factors or pre-term birth. Many people are unable to get adequate access to trained medical professionals and proper healthcare infrastructure. Often, the eye ailments remain undetected in the early stages, when taking proper prescriptions and precautions can prevent any further serious health issues. This paper proposes a medical diagnosis system for the automatic machine analysis of eye conditions including cataract, jaundice, and strabismus, along with a potent chatbot developed using Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques for and effective medical assistance. In cataract patients, the eye lens gets cloudy and hinders the proper vision. Jaundice is a liver disease, symptoms of which include yellowish eye. Strabismus is another eye condition when both eyes are not aligned symmetrically when focusing on any visual. The Convolutional Neural Network (CNN) models are developed and designed to attained an accuracy of 99.31%, 99.77% and 97.82% for detecting cataract, jaundice and strabismus respectively.