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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 classifying the data of female subjects taking the specific health examination is presented, using self-organizing maps (SOM's). The proposed method focuses on female subjects fulfilling the standard specified by body mass index and abdominal circumference. It defines the following data classes: the class with subjects of which hemoglobin A1c (HbA1c) values and item values...
To prevent lifestyle diseases, this paper studies disease prediction using periodical health checkup data, daily monitoring to maintain healthy condition, and early life disease detection with medical imaging. To analyse periodical health checkup data, three approaches are introduced. The first approach is based on fuzzy set. It converts all attributes of health checkup data into fuzzy degrees by...
This paper explores complex-valued multilayer perceptrons (MLPs) with the mechanism of stochastic resonance (SR). SR is a phenomenon such that a weak periodic signal in the system can be enhanced and detected in the presence of noises. It is expected that the combination of complex-valued encoding and SR mechanism will improve the performance of MLPs, rather than MLPs with either of them. The performances...
In this paper, methods of selecting formulas to calculate intraocular lens (IOL) power for a cataract patient are presented, using support vector machines (SVM's) and self-organizing maps (SOM's). Each of training data has measured values associated with axial length and corneal refractive power as element values. Three IOL power formulas have variables into which these values are substituted. The...
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