Abstract
This paper describes the development of a Rule Based Expert System (ES) to classify the Total Cholesterol (TC) level using Bioelectrical Impedance Analysis (BIA). A total of 199 voluntary subjects were recruited in the study. The BIA parameters that are statistically significant predictors are body capacitance (BC), basal metabolic rate (BMR) extracellular mass (ECM) and lean body mass (LBM). The ES was developed using Bayesian reasoning method. The developed ES is able to classify subjects’ TC level between normal (<=5.2 mmol/L) and abnormal (>5.2 mmol/L). From the analysis using 40 testing data, the system total accuracy for classifying TC level at 0.6 probability cutoff prediction was only 70.0%. The sensitivity was 67%, and specificity of 74%. From the validation data, this ES system can classify 6 from 10 subjects correctly.
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References
N. Paul Durrington Hyperlipidemia Diagnosis and Management. 2 nd Edition (1994)
Anthony E. Douglas, M.D, Cholesterol Test Department of Primary Care Internal Medicine Hospital of the University of Pennsylvania, Philadelphia. (2001)
Negnevitsky, M. Artificial intelligence, a guide to intelligent system, First Edition, Pearson education, ISBN: 0201711591 (2002)
Arie Ben-David, Leon Sterling, Generating rules from examples of human multiattribute decision making should be simple. Expert Systems with Applications 31 (2006) 390–396
Eraim Turban, Jay E. Aronson Decision Support System and Intelligent Systems, Sixth Edition, Prentice Hall, ISBN: 0130327239 (2001)
BIODYNAMIC 450-Biodynamics Model 450 Bioimpadance Analyzer user’s guide, “Basic Principles of Bioimpedance Testing”, First edition, copyright Biodynamics Corporation, pp. 1–22.
Stadtman, TC, Methods in Enzymology, Vol III, Colowick, SP, and Caplan, NO (Eds.), Academy Press New York, NY, 1957, pp 392–394,678–6
Lim TO et al. Clinical Research Centre Distribution of Blood Total Cholesterol in a National Sample of Malaysian Adults. (2000)
MS Mohktar, F. Ibrahim, NA Ismail, Effects of Abnormal Total Cholesterol Level on Bodycomposition Parameters, World Congress on Medical Physics and Biomedical Engineering, August 27–September 1, 2006, Seoul, Korea, Pages: 3628–3630.
Jerrold H. Zar, (1999) Biostatistical Analysis (Fourth Edition), Prentice Hall.
Marcello Pagano, Kimberlee Gauvreau (2000) Principles of Biostatistics, Duxbury, Thomson Learning.
Editorial, Bayesian networks in biomedicine and health-care, Artificial Intelligence in Medicine 30 (2004), 201–214
J.H. Orallo, C. Ferri, N. Lachiche, P. Flach, (2004), The 1st Workshop on ROC Analysis in Artificial Intelligence (ROCAI-2004), Volume 6, Issue 2-Page 159–161
Peter Lucas, Bayesian Networks in Medicine: a Model-based Approach to Medical Decision Making, University of Aberdeen, Scotland, UK, (2000)
K.S Metaxiotis, J.E Samouilidis, (2000), Expert System in Medicine: Academic Illusion or Power, Information Management & Computer Security, 8/2, Page 75–7
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Mohktar, M.S., Ibrahim, F., Ismail, N.A. (2007). Expert System for Non-Invasive Classification of Total Cholesterol Level Using Bioelectrical Impedance. In: Ibrahim, F., Osman, N.A.A., Usman, J., Kadri, N.A. (eds) 3rd Kuala Lumpur International Conference on Biomedical Engineering 2006. IFMBE Proceedings, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68017-8_17
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DOI: https://doi.org/10.1007/978-3-540-68017-8_17
Publisher Name: Springer, Berlin, Heidelberg
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