An Innovative Medical System To Reduce Mortality Rates

Abstract: Now a day’s patient deaths increasing rapidly because of many chronic diseases and many other factors like diseases, lack of medical facilities, resources, medicines etc. According to the number of mortality from public health statistics data of the Strategy and Planning Division, had been increasing consecutively every year, so health service is the most important task to reduce the mortality rate for the country population. It’s a challenging factor to reduce the death rates in a hospital. So we need a system which will automatically detect the reasons for death rates. The purpose of this project is to show an association between mortality rates and health services or resources by using unsupervised machine learning algorithms. This is what we are doing in the proposed system where we find the relationship between hospital resources and mortality rates. We build a real time system using Microsoft technologies such as Visual Studio and SQL server to help hospitals to reduce death rates. We consider many parameters like Neurologist, Cardiologist, Gynecologist, Orthopedics, Surgeon, Physician, Beds, ICU, Nurses and Mortality Rate. Also system finds the most important parameter which increases the death rates using ML algorithms.

Keywords: Data Science, Machine Learning, Association Learning, Mortality Rates, Visual Studio, SQL Server