摘要：The abdominal obesity is strongly associated with increased risk of obesity-related cardiometabolic disturbances. The proportion of waist circumference and body height,known as waist-toheight ratio (WHtR),has been shown as a good risk indicator related with abdominal obesity. This paper presents a solution based on artificial neural networks (ANN) for determining WHtR limit for predicting hyperglycemia in obese persons. ANN inputs are body mass index (BMI) and glycemia (GLY),and output is weist-to-height ratio (WHtR). ANN training and testing are done by dataset that includes 1281 persons.
