Evaluation of Data Mining Algorithms for Detection of Liver Disease

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SHAHRAKI MOHAMMAD REZA; Mesgar Mahboubeh

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Journal: Payavard Salamat Year:2019 | Volume:13 | Issue:1 Page(s): 81-90

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Information Journal Paper

Title

Evaluation of Data Mining Algorithms for Detection of Liver Disease

Author(s)

SHAHRAKI MOHAMMAD REZA | Mesgar Mahboubeh | Issue Writer Certificate

Keywords

Liver DiseaseQ1

Support Vector Machine (SVM)Q1

CHAID AlgorithmsQ1

C5.0 Decision TreeQ1

Data MiningQ1

Abstract

Background and Aim: The liver, as one of the largest internal organs in the body, is responsible for many vital functions including purifying and purifying blood, regulating the body's hormones, preserving glucose, and the body. Therefore, disruptions in the functioning of these problems will sometimes be irreparable. Early prediction of these diseases will help their early and effective treatment. Regarding the importance of Liver Diseases and increasing number of patients, the present study, using Data Mining algorithms, aimed to predict Liver Disease. Materials and Methods: This descriptive study was performed using 721 data from liver patients from Zahedan. In this study, after preprocessing data, Data Mining techniques such as SVM: Support Vector Machine, CHAID, Exhaustive CHAID and boosting C5. 0, data were analyzed using IBM SPSS Modeler 18 Data Mining software. Result: According to the findings, the Liver Diseases can be predicted by the enhanced C5. 0 algorithm with precision of 94/09, exhaustive CHAID algorithm with precision of 88/71, SVM with the precision of 87/09, and CHAID algorithm with the precision of 85/47. The enhanced C5. 0 algorithm showed the best performance among other algorithms. Conclusion: According to the rules created by boosting C5. 0 algorithm, for a new sample, one can predict the likelihood of a person for developing Liver Disease with high precision.

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APA: Copy

SHAHRAKI, MOHAMMAD REZA, & Mesgar, Mahboubeh. (2019). Evaluation of Data Mining Algorithms for Detection of Liver Disease. PAYAVARD-SALAMAT, 13(1 ), 81-90. SID. https://sid.ir/paper/366765/en

Vancouver: Copy

SHAHRAKI MOHAMMAD REZA, Mesgar Mahboubeh. Evaluation of Data Mining Algorithms for Detection of Liver Disease. PAYAVARD-SALAMAT[Internet]. 2019;13(1 ):81-90. Available from: https://sid.ir/paper/366765/en

IEEE: Copy

MOHAMMAD REZA SHAHRAKI, and Mahboubeh Mesgar, “Evaluation of Data Mining Algorithms for Detection of Liver Disease,” PAYAVARD-SALAMAT, vol. 13, no. 1 , pp. 81–90, 2019, [Online]. Available: https://sid.ir/paper/366765/en

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