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In this paper, an application of self-organizing maps (SOM's) in classifying and predicting data of female subjects with unhealthy-level visceral fat is discussed. The proposed method chooses subjects fulfilling the standard specified by body mass index and abdominal circumference. It defines the class with subjects of which hemoglobin A1c (HbA1c) values and item values associated with a liver deteriorate,...
In this paper, a method of analyzing relationships between items in specific health examination data is presented to cope with lifestyle-related diseases. The proposed method uses self-organizing maps, and focuses on twelve items such as hemoglobin A1c (HbA1c), glutamic-oxaloacetic transaminase (GOT), glutamic-pyruvic transaminase (GPT), gamma-glutamyl transpeptidase (γ-GPT), and triglyceride (TG)...
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