Exploration of the Impact of Remote work and Online Education on Visual Health during the COVID-19 using Machine Learning Approaches

The COVID-19 pandemic has been associated with several manifestations that affect an individual’s visual health. To address these concerns, we propose a classification model to predict the impact of COVID-19 on vision. The model is built on a dataset corresponding to visual symptoms and other factors. The proposed classification model will classify people into three categories: those with no impact on vision, those with mild-to-moderate impact, and those with severe impact. Some machine learning algorithms, such as logistic regression, decision trees, random forests, etc., were applied by us to build the model to identify the optimal algorithm for the task. The results obtained from the model show that it has high accuracy, precision, and recall. The model can predict the severity of visual symptoms in people due to COVID-19 with an accuracy of over 84%. The study findings are entirely focused on the E-learning or online learning caused due to COVID-19 pandemic and their impact on vision of people from different age groups.