Abstract:
Machine learning is currently playing a very important role in various sectors. It also has a
significant position in the healthcare sector for its working efficiency. Machine learning
classification algorithms are popular in medical science for predicting various complex
diseases. Kidney disease is a familiar name to all of us nowadays. Moreover, this disease
has become a major public health problem for people worldwide. People are affected with
kidney disease when they do not follow a proper diet in their daily life, lack of proper health
awareness including drinking a very little amount of water. As a result, the disease later
turned into a terrible disease, which is called CKD. Countless people all over the world are
suffering from this disease and they are dying due to a lack of proper awareness and
treatment. The treatment of this disease is extremely expensive and difficult. When a
patient is affected with CKD, their kidneys stop working completely. There is no limit to
the suffering of patients when the kidneys stop their activity. In this research, we have tried
to predict CKD by applying various classification algorithms of machine learning.
Accurate data is very important to do this work so that we have done this work with the
proper dataset. Our goal is to identify and predict chronic kidney disease. To predict CKD,
we used four popular machine learning classification algorithms. Which are respectively
SVM, Decision Tree, Random Forest, KNN. We have basically completed our work in two
steps. In the first step we have completed the training of the data and in the next step
completed the testing. After trained by the machine learning algorithm, we got our desired
result. In that case, the Decision tree algorithm has shown the best performance among the
four classification algorithms.
