Browse > Article
http://dx.doi.org/10.3745/KTSDE.2019.8.11.433

Prediction Model for Hypertriglyceridemia Based on Naive Bayes Using Facial Characteristics  

Lee, Juwon (한국한의학연구원 미래의학부)
Lee, Bum Ju (한국한의학연구원 미래의학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.8, no.11, 2019 , pp. 433-440 More about this Journal
Abstract
Recently, machine learning and data mining have been used for many disease prediction and diagnosis. Chronic diseases account for about 80% of the total mortality rate and are increasing gradually. In previous studies, the predictive model for chronic diseases use data such as blood glucose, blood pressure, and insulin levels. In this paper, world's first research, verifies the relationship between dyslipidemia and facial characteristics, and develops the predictive model using machine learning based facial characteristics. Clinical data were obtained from 5390 adult Korean men, and using hypertriglyceridemia and facial characteristics data. Hypertriglyceridemia is a measure of dyslipidemia. The result of this study, find the facial characteristics that highly correlated with hypertriglyceridemia. FD_43_143_aD (p<0.0001, Area Under the receiver operating characteristics Curve(AUC)=0.652) is the best indicator of this study. FD_43_143_aD means distance between mandibular. The model based on this result obtained AUC value of 0.662. These results will provide a basis for predicting various diseases with only facial characteristics in the screening stage of disease epidemiology and public health in the future.
Keywords
Machine Learning; Facial Characteristics; Hypertriglyceridemia; Predictive Model;
Citations & Related Records
연도 인용수 순위
  • Reference
1 R. Chitra and V. Seenivasagam, "Heart Disease Prediction System using Supervised Learning Classifier," Bonfring International Journal of Software Engineering and Soft Computing, Vol.3, No.1, pp.1-7, 2013.   DOI
2 J. Soni, U. Ansar, D. Sharma, and S. Soni, "Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction," International Journal of Computer Applications, Vol.17, No.8, pp.43-48, 2011.   DOI
3 B. J. Lee and J. Y. Kim, "Indicators of Hypertriglyceridemia from Anthropometric Measures Based on Data Mining," Computers in Biology and Medicine, Vol.57, pp.201-211, 2015.   DOI
4 B. J. Lee, J. H. Do, and J. Y. Kim, "A Classification Method of Normal and Overweight Females Based on Facial Features for Automated Medical Applications," BioMed Research International, pp.1-9, 2012.
5 B. J. Lee and J. Y. Kim, "Predicting Visceral Obesity Based on Facial Characteristics," BMC Complementary and Alternative Medicine, Vol.14, No.248, 2014.
6 M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. Witten, "The WEKA Data Mining Software: an Update," ACM SIGKDD Explorations Newsletter, Vol.11, No.1, pp.10-18, 2009.   DOI
7 T. M. Mitchell, "Machine Learning," McGraw-Hill, pp. 154-200, 1997. BioMed Research International, pp.1-9, 2012.
8 C. Beyene and P. Kamat, "Survey on Prediction and Analysis the Occurrence of Heart Disease Using Data Mining Techniques," International Journal of Pure and Applied Mathematics, Vol.118, No.8, pp.165-174, 2018.
9 M. A. Hall, "Correlation-based Feature Selection for Machine learning," Ph. D. Dissertation, University of Waikato, Hamilton, NewZealand, 1999.
10 M. Hall and G. Holmes, "Benchmarking Attribute Selection Techniques for Discrete Data Class Data Mining", IEEE Trans. Knowl. DataEng., Vol.15, No.6, pp.1437-1447, 2003.   DOI
11 R. Kohavi and G. H. John, "Wrappers for Feature Subset Selection," Artificial Intelligence, Vol.97, Issues 1-2, pp.273-324, 1997.   DOI
12 I. Guyon and A. Elisseeff, "An Introduction to Variable and Feature Selection," Journal of Machine Learning Research, Vol.3. pp.1157-1182, 2003.
13 N. Tan, M. Steinbach, and V. Kumar, "Introduction to Data Mining," Addison-Wesley Longman pub, Boston, pp.295-304, 2006.
14 A. H. Chen, S. Y. Huang, P. S. Hong, C. H. Cheng, and E. J. Lin, "HDPS: Heart Disease Prediction System," 2011 Computing in Cardiology. IEEE, pp.557-560, 2011.
15 E. G. Jeong, "The Status and Issues of Chronic Diseases (2018)", Korea Centers for Disease Control & Prevention(KCDC), 2018.
16 G. Kaur and A. Chhabra, "Improved J48 Classification Algorithm for the Prediction of Diabetes," International Journal of Computer Applications, Vol.98, No.22, pp.13-17, 2014.   DOI