Data mining approaches for kidney dialysis treatment

SRIRAAM, N. (2006) Data mining approaches for kidney dialysis treatment. Journal of Mechanics in Medicine and Biology, 6 (2). pp. 109-121. ISSN 02195194

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Official URL: http://dx.doi.org/10.1142/S0219519406001893

Abstract

Data mining techniques has been used as a recent trend for achieving diagnostics results, especially in medical fields such as kidney dialysis, skin cancer and breast cancer detection, and also biological sequences classification. Due to its ability to discover the relationship and pattern of the medical database, early detection or prediction of pathological conditions through mining has become feasible. This paper discusses the data mining approach for parametric evaluation to improve the treatment of kidney dialysis patient. The experimental result shows that classification accuracy using Association mining between the ranges 50-97.7% is obtained based on the dialysis parameter combination. Such a decision-based approach helps the clinician to decide the level of dialysis required for individual patient.

Item Type: Article
Subjects: Q Science > QC Physics
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 23 Sep 2011 03:22
Last Modified: 23 Sep 2011 03:22
URI: http://shdl.mmu.edu.my/id/eprint/1965

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