Assessment of Chronic Kidney Disease using clustering techniques - Dalui, Debolina; Karmakar, Priyabrata; Singh, Dharmpal; Bhattacharyya, Sonali (International Journal of Computer Sciences and Engineering, 2025)
Data mining is the process of extracting hidden interesting patterns from massive database. It is used to extract the hidden information/knowledge /inference from the real-life database. In this paper an effort has been made to implement the concept of data mining in Chronic Kidney Disease. Chronic Kidney Disease contains heterogeneous data that can be mined properly to provide a variety of useful information for the physicians to detect a disease and predict the severity of the disease and above all survivability of the patients who have this disease. The concepts of clustering and data mining have been used to design the knowledge base for the prediction of chronic kidney disease based on the new data. The concept of factor analysis has been used for the selection of the best factor of this data set and there after the concept of clustering has been used to predict the output of new data element of same data set.