Abstract:
In this project I had developed a system based on machine learning that helps to detect a
Heart, Kidney and Liver disease of a person. The idea for this project is derived from IEEE
papers. The papers suggest Random Forest Classifier for developing such a system. I also
referred another IEEE paper which uses Machine Learning to deal with this. Random forest
is a Supervised Machine Learning Algorithm that is used widely in Classification and
Regression problems. It builds decision trees on different samples and takes their majority
vote for classification and average in case of regression. One of the most important features of
the Random Forest Algorithm is that it can handle the data set containing continuous
variables as in the case of regression and categorical variables as in the case of classification.
It performs better results for classification problems.
The aim is to develop an application that will detect heart, kidney and liver diseases. In the project,
we have to detect whether a person has heart disease or not. Then if the person has heart
disease, we provide necessary recommendations. Also, we have to predict whether a person
has kidney disease or not. Then if the person has Kidney disease, we provide necessary
recommendations. Diet recommendation for patient will be given according to potassium
zone which is calculated using blood potassium level to slow down the progression of CKD. There
are 3 zones that are defined for kidney disease patients. They are safe zone, caution zone and
Danger zone. Similar case in liver diseases prediction. We have to detect whether a person has
liver disease or not. If the person has liver disease, necessary recommendations are provided.
