End-to-End Encryption and Prediction of Medical Insurance Cost

Abstract

Health-care costs are rising on a daily basis after the advent of Covid. Most importantly, health issues are becoming more prevalent and critical. As a result, predicting medical insurance cost has become unavoidable as many people choose insurance. However, for a secure system, the entire prediction model for each customer should be encrypted end-to-end. To create a better prediction model, Machine learning regression algorithms are used. The prediction model will be encrypted end-to-end. This paper will give the steps of developing a reliable medical insurance cost prediction model.