Health Monitoring System Using Machine Learning Techniques Algorithm

Health Monitoring System Using Machine Learning Techniques Algorithm

Prof. Pragati Patil, Rutika Bhagat

1Project Guide, Department of Computer Science Engineering, Abha Gaikwad Patil College of Engineering, Nagpur.

2Students, Department of Computer Science Engineering, Abha Gaikwad Patil College of Engineering, Nagpur.

Abstract
A person's health is one of the most important factors in his or her ability to move forward in life. The goal of the health-care system is to improve the population in the most efficient way possible, given society's available resources and needs. Death rates are rising in the majority of countries due to a lack of timely medical instruments and treatments. By providing standard health care services, these health risks can be avoided. Our Health Monitoring System is a Web Application built with the Flask framework. We used Decision Tree Classification (Supervised Machine Learning technique) in this Health Monitoring System to predict results accurately. To train and evaluate our model, we used our own dataset. We would be able to predict the patient's health level and area of risk based on that evaluation.

Keywords— Health Monitoring System, Decision tree algorithm, Flask, Risk level. etc.