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Data Mining Model Approach for The Risk Factor of BMI - By Medical Examination of Health Data -

  • Lee Jea-Young (Department of Mathematics and Statistics, Yeungnam University) ;
  • Lee Yong-Won (Institute of Medical Science, Yeungnam University College of Medicine)
  • Published : 2005.04.01

Abstract

The data mining is a new approach to extract useful information through effective analysis of huge data in numerous fields. We utilized this data mining technique to analyze medical record of 35,671 people. Whole data were assorted by BMI score and divided into two groups. We tried to find out BMI risk factor from overweight group by analyzing the raw data with data mining approach. The result extracted by C5.0 decision tree method showed that important risk factors for BMI score are triglyceride, gender, age and HDL cholesterol. Odds ratio of major risk factors were calculated to show individual effect of each factors.

Keywords

References

  1. M. Baglion, U. Ferrara, A. Romei, S. Ruggier, F. Turini (2003). Preprocessing and Mining Web log Data for Web Personalization Proc. of 8th Natl' Conf. of the Italian Association for Artificial Intelligence (AI*IA 2003), Paris (to be held September 2003), Italy
  2. WHO (1997) Preventing and managing the global epidemic, Report of a WHO Consultation on Obesity, Geneva, 3-5 Jun. 1997
  3. WHO, West Pacific Region. The Asia-Pacific Perspective: Refining Obesity and its Treatment. IOTF. Feb. 2000
  4. 이성원 (2001). Logistic modelling for receiver operation characteristic curves with neural networks, Ph.D, 영남대학교
  5. 오희숙, 천병렬, 감신, 예민혜, 강윤식, 김건엽, 이영숙, 박기수, 손재희, 이상원, 안문영 (2000). 농촌지역 주민들의 고혈압 발생 위험요인:1년간 전향적 추적 조사. 예방의학회지 Vol.33 No.2 p.231-238
  6. 이성희 (2001). 비만이 고혈압 발생에 미치는 영향에 관한 후향적 코호트 연구. Ph.D 서울대학교
  7. 최병권 (2004). 데이터 마이닝 기법을 이용한 제조업 부도예측 주요 변수 선택, 서울대학교
  8. 탁양주, 이영성, 이진석, 강재현 (2004). 최근 국내 비만 연구의 경향:1984년부터 2002년까지. 대한비만학회지 Vol.13 No.1 p.1-8
  9. 허명회, 이용구 (2003). 데이터 마이닝 모델링과 사례, SPSS 아카데미 p.29, 144-178