Analysis of Risk Factors and Severity of Osteoarthritis from Risk Behaviors to Osteoarthritis Using Data Mining Techniques

Authors

  • Benyapha Srisawang Faculty of Information Technology, Sripatum University
  • Surasak Mungsing Faculty of Information Technology, Sripatum University

Keywords:

Osteoarthritis, Data mining techniques, Data classification, Severity prognosis

Abstract

The purpose of this research was to study and analyze the data of those at risk of osteoarthritis and the severity of those suffering from osteoarthritis from behaviors at risk of developing osteoarthritis. Data were collected from a sample of 151 patients with osteoarthritis of the knee and a sample of 113 without osteoarthritis. The data used in the analysis were collected between March and June 2021 and were analyzed using four data mining techniques: Decision tree (J48), Naïve bayes, SMO and Neural network to find correlation between behavioral data and knee pain levels in people with osteoarthritis The results showed that the Naïve bayes algorithm was able to generate the most efficient models with an accuracy of 95.8115 %

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Published

2022-10-22

How to Cite

Srisawang, B. ., & Mungsing, S. . (2022). Analysis of Risk Factors and Severity of Osteoarthritis from Risk Behaviors to Osteoarthritis Using Data Mining Techniques. Journal of the Thai Medical Informatics Association, 8(2), 61–67. Retrieved from https://he03.tci-thaijo.org/index.php/jtmi/article/view/479

Issue

Vol. 8 No. 2 (2022): July-December

Section

Articles