Identifying the Most Important Factors in Determining the Osteoporosis in Women Using Data Mining Techniques

Mohammad Reza Salamat; Amir Hossein Salamat; Mohammad Sattari; Saeed Saeedbakhsh; Mehdi Asgari

doi:10.18502/acta.v61i4.13174

Mohammad Reza Salamat Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
Amir Hossein Salamat Research and Development Division, Osteoporosis Diagnosis Center, Isfahan, Iran
Mohammad Sattari Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
Saeed Saeedbakhsh Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
Mehdi Asgari Department of Nursing, School of Nursing, Larestan University of Medical Sciences, Larestan, Iran

DOI: https://doi.org/10.18502/acta.v61i4.13174

Keywords: Data mining; Osteoporosis; Women

Abstract

Osteoporosis is one of the primary causes of disability and mortality in the elderly. If osteoporosis's significant features can be identified, the risk of developing this disease will be reduced. In recent years, data mining approaches have become a suitable tool for medical researchers. This study applied data mining methods to identify osteoporosis’s significant features. This study applied data from women having osteoporosis or osteopenia in the period 2011-2019 in the Osteoporosis Diagnosis Center, Isfahan, Iran. Data mining methods such as linear regression, naïve bayes, decision tree, support vector machine, random forest, and neural network were implemented on the dataset. This study consisted of 8258 patients’ information, of which 1482 had osteoporosis. The results showed that the support vector machine, decision tree, neural network are the best method based on accuracy, precision, and AUC measures. Six candidate features were age, weight, back pain, low activity, menopause date, and previous fracture. Support vector machine, decision tree, and neural network are the best candidate techniques for predicting osteoporosis. Thin older people are more at risk of osteoporosis than other people. Yet, people with middleweight and middle age are at lower risk of osteoporosis.