Study and analysis of COVID-19 patients using machine learning methods

Abstract EN

Machine Learning (ML) systems has been used in healthcare to recognize and diagnose diseases using patient’s data.

The use of ML in technology has reformed and improved healthcare by automatically detecting and diagnosing diseases which in turn improve patient’s health and saves lives.

Therefore, in this study, ML algorithms are used to predict death and recovery of patients.

Using several ML algorithms the death or recovery of patients was predicated.

The Naïve Bayes and Bagged Trees algorithms provided the best performance rates of 79% and 77% respectively.

However, in terms of accuracy, the Medium Tree and ensemble method Boosted Tree classification algorithms showed 89% accuracy.

This study showed that using ML technology could alert healthcare providers to provide faster treatment for high risk COVID-19 patients which in turn save lives and improve quality of healthcare service.