Research of Chronic Kidney Disease based on Data Mining Techniques

Thiyagaraj, M. and Suseendran, G. (2019) Research of Chronic Kidney Disease based on Data Mining Techniques. International Journal of Recent Technology and Engineering, 8 (2S11). pp. 115-120. ISSN 2277-3878

[thumbnail of B10190982S1119.pdf] Archive
B10190982S1119.pdf

Download (325kB)

Abstract

Research of Chronic Kidney Disease based on Data Mining Techniques

Kidney disease is one of the real general medical issues these days. Ceaseless ailments prompt to horribleness and mortality in India and furthermore in the low pay and center nation. The interminable infections on record is 60% of death all through the around the world. 80% of unending malady passing overall additionally happen in low and center pay nations. In India, most likely the quantity of passing is because of the ceaseless ailment observed to be 5.21 million in 2008 and is by all accounts brought to 7.63 million up in 2020 roughly 66.7%. Information mining is the procedure of extraction is the concealed data from the given expansive dataset. Different information mining strategies, for example, bunching, characterization, affiliation investigation, relapse, outline, time arrangement examination and succession investigation were utilized to anticipate kidney maladies. The strategies that were presented so far had minor downsides in the nature of pre handling or at some other stages. In this paper, the different information mining methods are reviewed to foresee kidney sicknesses and real issues are quickly clarified
11 2 2019 115 120 B10190982S1119 10.35940/ijrte.B1019.0982S1119 https://www.ijrte.org/wp-content/uploads/papers/v8i2S11/B10190982S1119.pdf https://www.ijrte.org/wp-content/uploads/papers/v8i2S11/B10190982S1119.pdf

Item Type: Article
Subjects: Information Technology > Databases
Divisions: Information Technology
Depositing User: Mr IR Admin
Date Deposited: 06 Oct 2024 05:49
Last Modified: 06 Oct 2024 05:49
URI: https://ir.vistas.ac.in/id/eprint/8761

Actions (login required)

View Item
View Item