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Large imbalanced datasets have introduced difficulties to classification problems. They cause a high error rate of the minority class samples and a long training time of the classification model. Therefore, re-sampling and data size reduction have become important steps to pre-process the data. In this paper, a sampling strategy over a large imbalanced dataset is proposed, in which the samples of...
In this paper, we develope a genetic algorithm based fuzzy inference system to recognize hypoglycemic episodes based on heart rate and corrected QT interval of the electrocardiogram (ECG) signal. Genetic algorithm is introduced to optimize the membership functions and fuzzy rules. A practical experiment based on data from 15 children with T1DM is studied. All the data sets are collected from the Department...
Low blood glucose (Hypoglycaemia) is dangerous and can result in unconsciousness, seizures and even death. It has a common and serious side effect of insulin therapy in patients with diabetes. We measure physiological parameters (heart rate, corrected QT interval of the electrocardiogram (ECG) signal, change of heart rate, and the change of corrected QT interval) continuously to provide detection...
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