An Innovative Approach to Predict Refractive Error of a Human Eye using Machine Learning

According to a research study, about 53.1% of the people are affected by refractive error in their eyes which can be treated either temporarily or permanently. To identify this error in the human eye, this research has been exhibited on machine learning algorithms that studies a dataset and finds a pattern that wasn't obvious by using statistical methods. Generally, from the disability in clear vision. it can be identified that a person has some refractive error. By performing a reading test, the user's eye vision may be predicted, using the refractive error from their eyes to the laptop or computer i.e., screen distance. Accurately predicting refractive error as myopia, hyperopia, presbyopia and astigmatism in users is not easy. Refractive errors can lead to permanent visual disorder, but is possibly curable if the user can detect the error at the earliest. Various machine learning tools have been adopted to more easily screen a large number of patients for refractive error identification. By comparing different algorithms. the most accurate algorithm to detect the refractive error is defined and the same is used in this work.