Surveying the knowledge of pregnant women towards sport activities during pregnancy using data mining algorithms

Yıl 2016, Cilt: 18 Sayı: 1, 8 - 16, 07.04.2016

Fatemeh Islamı Fatemeh Bagherı Fatemeh Mohammadı

https://doi.org/10.15314/tjse.30959

Cited By: 1

Öz

The purpose of this study is to research the knowledge of pregnant women towards sport activities using data mining algorithms. Statistical population includes all healthy pregnant women referring to health centers in Gorgan city (Iran) in 2014 from which 429 were chosen as the sample using cluster random sampling. The questionnaire included 65 questions in 6 sections each relating to one knowledge level. Data related to each knowledge level were categorized by decision tree algorithms (CHAID, CART C5.0, QUEST) to predict general knowledge with 3 knowledge descriptions (good, medium, poor) and 5 knowledge descriptions (very good, good, medium, poor, very poor) and then were compared. Also the relationship of these knowledge levels was compared using regression algorithms and SVM. Results show that most of the population has a good and medium knowledge and their knowledge about sport during pregnancy is suitable. In predicting the level of knowledge using decision tree in both prediction level (5 label and 3 label), C5.0 algorithm had the most accurate prediction. Also in comparison, SVM algorithm and SVM regression algorithm had better results with the least error. As a result, it can be said that Extracted rules from algorithms helps to estimating the level of knowledge faster than traditional statically way and provide education regarding exercises during pregnancy for the health of mother and fetus.

 

Anahtar Kelimeler

Data mining; decision trees; pregnancy; knowledge of exercise

Kaynakça

• Abedzadeh M, Taebi M, Sadat Z, Saberi F. Knowledge and performance of pregnant women referring to shabihkhani hospital on exercises during pregnancy and postpartum periods. Pars journal of Medical Sciences, 2011; 8(4): 43-48. [Persian]
• Al Jarullah, Asma A. Decision tree discovery for the diagnosis of type II diabetes. In Innovations in Information Technology (IIT), 2011 International Conference on, 2011; pp. 303‐307. IEEE.
• Alizadeh S, Malekmohmmadi S. Data mining step by step. Tehran, K.N.Toosi University of Technology Press; 2001. [Persian]
• Bagheri F, Alizadeh Majd H, Mehrbakhsh Z, Ziaratban M. Use of data mining algorithms in assessing the affecting factors on predicting the health status of newborns. Hakim Jorjani J. 2015; 2(2): 59-68. [Persian]
• Chattamvelli R, Data mining Algorithm, Alpha science, 2011.
• Dabirian S, Daneshvarfard M, Hatmi ZN. To assess the performance of exercise during pregnancy. Iranian Journal of Epidemiology, 2009; 5(3): 22-26. [Persian]
• Dogaru R, Zaharie D, Lungeanu D, Bernad E, Bari M. A Framework for Mining Association Rules in Data on Perinatal Care. The 8th International Conference on Technical Informatics. Timisoara, Romania, 2008.
• Fang X. Are you becoming a diabetic? A data mining approach. In Fuzzy Systems and Knowledge Discovery, 2009. FSKD'09. Sixth International Conference on, 2009; 5: 18‐22. IEEE.
• Ghazanfari M, Alizadeh S, Teymurpour B. Data Mining and Knowledge Discovery. Tehran, Iran University of Science and Technologh Press; 2014. [Persian]
• Goodwin LK, Iannacchione MA, Hammond WE, Crockett P, Maher S, Schlitz K. Data mining methods find demographic predictors of preterm birth. Nurs Res, 2001; 50(6): 340-345.
• Goodwin LK, Iannacchione MA. Data mining methods for improving birth outcomes prediction. Outcomes Manag, 2002; 6(2):80-5.
• Islami F, Khoran MT. Knowledge and Performance of Pregnant Women towards Sport Activities during Pregnancy. Final Report of Research project. Golestan University. 2014. [Persian]
• Moghaddassi H, Hoseini A, Asadi F, Jahanbakhsh M. Application of Data Mining. Health Information Management, 2012; 9(2): 304. [Persian]
• Noohi E, Nazemzadeh M, Nakhei N. The study of knowledge, attitude and practice of puerperal women about Exercise during pregnancy. Iran Journal of Nursing (IJN), 2010; 23(65): 33-41. [Persian]
• Rahimi S, Seyed Rasouli A. Pregnant Women and Exercise. Iran Journal of Nursing, 2004; 17(40): 6-10. [Persian]
• Thongkam J, Xu G, Zhang Y, Huang F. Support vector machines for outlier detection in cancers survivability prediction. In International Workshop on Health Data Management, APWeb’08 2008; 99-109.
• Zand S, Zamani A. The Effect of Simple Exercise Maneuvers and Proper Performance of Daily Activity on Outcome of Pregnancy. Iranian Journal of Obstetrics, Gyneocology and Infertility, 2009; 12(3): 51-57. [Persian]