Medical dialysis prediction using fuzzy rules

Medical diagnosis is normally done by the experts. But still many cases are reported of erroneous diagnosis and wrong treatment. Patients advised to undergo a lot of tests for treatment. In many circumstances, not all the tests add towards proper diagnosis of a disease. The objective of this work is to predict the dialysis requirement of a patient by diagnosing the number of attributes related to kidney functionality at the earlier stage. As the medical and related data keeps on growing day by day, it is difficult to predict about a disease that a patient may be diagnosed with. The effective prediction about a disease and its related diagnosis can be determined based on the particular patient´s past medical history. The past medical history can be extracted from the database and the patient can be diagnosed accordingly. In this paper, we are extracting data from database related to various parameters required to identify the functioning of kidney and then predicting the functionality of the kidney. Based on the current functionality of the kidney, the dialysis requirement can be effectively predicted.