Research of Chronic Kidney Disease based on Data Mining Techniques
M. Thiyagaraj1, G. Suseendran2
1M. Thiyagaraj, Ph.D, Research Scholar, Department of Information and Technology, Vels Institute of Science, Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
2G. Suseendran, Assistant Professor, Department of Information and Technology, Vels Institute of Science, Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
Manuscript received on 10 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 02 November 2019 | PP: 115-120 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10190982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1019.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Chronic Kidney Disease (CKD), Risk Factors of CKD, Challenging Issues of CKD and Data Mining and Machine Learning (ML) Algorithms.
Scope of the Article: Data Mining