PATIENT’S SICKNESS PREDICTION SYSTEM

As we have seen in the recent years how people have suffered across the globe in the pandemic where corona virus has affected almost every part of the world. Similarly, we too have faced the pandemic and people almost of all age groups were affected because of the restrictions and virus. As the regular OPDs were closed and the beds were occupied it became difficult for the patients specially those who were having their routine checkup at regular intervals so overcome that we got the idea of patient sickness prediction system using multiple Machine learning algorithms. Here in this work on the basis of symptoms, age, and gender of an individual, it gives the output as sickness from which patient might be suffering from early and accurately allows for effective and efficient treatment, which will provide them relief. This paper presents a brief analysis of patient sickness using Naive Bayes technique, Decision tree and Random Forest methodology.