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KMID : 0365220120490020088
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Korean Journal of Public Health
2012 Volume.49 No. 2 p.88 ~ p.98
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Computational Approach for Understanding Diabetes Mellitus
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Yoon Jae-Moon
Son Hyeon-Seok
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Abstract
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Knowledge of diabetes mellitus has been consistently accumulated through numerous epidemiological and experimental studies. For the faster accumulation of the knowledge from recent researches, the need for computational implementations and integrations has appeared. Indeed, computational methods are already used to research various aspects of diabetes mellitus, such as pathology, diagnosis, treatments, complications, and expenditures. Researchers have used phylogenetic tree analysis and network based analysis for pathology and association studies each. Clustering techniques including neural network and support vector machine were used for the diagnosis of diabetes mellitus. Predictions of three-dimensional structure of proteins were performed and decision support models were also conducted. Markov models were used for the cost-effectiveness analysis. More convenient user interface of computational applications is also concerned. In this review, we summarized previous studies of computational methods and suggested further applications for diabetes researches.
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KEYWORD
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Diabetes, Computational pathology, Computational medical application, Bioinformatics
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