Diagnose of chronic kidney diseases by using naive Bayes algorithm

Abstract EN

Chronic kidney disease (CKD) develops gradually, usually after months or years when the kidneys lose function.

In general, it may not be detected before it loses 25% of its functionality.

Patients may begin to not recognize kidney failure because kidney failure may not give any symptoms at first.

Treatment for kidney failure aims to control the causes and slow the progression of kidney failure.

If the treatments are insufficient, the patient is in the end stage of kidney failure and the last treatment is dialysis or a kidney transplant.

at this time.

Therefore, it is necessary to make an early diagnosis to avoid reaching the stage of kidney failure.

We conclude in this paper that the Naive Bayes algorithm is one of the best algorithms for diagnosing diseases with high accuracy of 99.24% and time of 0.003 seconds approximately because it is suitable for this kind of dataset.