Key result
A genetic algorithm-based multiple regression with fuzzy inference system using heart rate and QT intervals detected nocturnal hypoglycemic episodes with good sensitivity and acceptable specificity in 16 children with T1DM.
Why the study?
Does a GA-based multiple regression with FIS using HR and QT interval accurately detect nocturnal hypoglycemic episodes in children with T1DM?
Population
16 children with type 1 diabetes mellitus (T1DM)
Authors
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May support ECG-based nocturnal hypoglycemia detection in pediatric T1DM; leaves open validation in larger prospective studies.
Does a GA-based multiple regression with FIS using HR and QT interval accurately detect nocturnal hypoglycemic episodes in children with T1DM?
A novel algorithm using heart rate and corrected QT interval can detect nocturnal hypoglycemia in children with type 1 diabetes.
Ling et al. (2011) studied Type 1 diabetes mellitus (n=16). Genetic algorithm-based multiple regression with fuzzy inference system was evaluated on Detection of nocturnal hypoglycemic episodes. A genetic algorithm-based multiple regression with fuzzy inference system using heart rate and QT intervals detected nocturnal hypoglycemic episodes with good sensitivity and acceptable specificity in 16 children with T1DM.
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