Predict the Readmission Patterns of Chronic Diseases Using Machine Learning

Abstract

Machine learning plays an essential role in  predicting presence or obsence of locomotor disorders. The  diseases like heart, diabetes, cancer, kidney we collect data  and such information if predicted well in advance can  provide important insights to doctors who can adapt their  diagnosis and treatment per patient basis. Here comes to  heart disease alternatively known as cardiovascular disease,  encases various conditions that impact the heart is the  primary basis of death worldwide over the span of the past  few decades. when we come to the disease like diabetes  which is among critical disease and lot of people are  suffering from this disease. People having diabetes, kidney disease, heart stroke and nerve damage. Cancer disease is  very dangerous and critical. Kidney disease also recognized  as chronic renal disease, is an uncharacteristic functioning  of kidney or a failure of renal function expanding over a  period of months or years and it is detected during the  screening of people who are known to be in threat by  kidney problems. So, the early prediction is necessary in  combating these diseases and to provide good treatment.  For predicting these diseases in people, we are using  machine learning techniques.