Refined DiaData with IQR outlier handling and Stineman interpolation enables ResNet to classify hypoglycemia onset up to 2 hours ahead, with 2-3% gain from data quality and 7% from more data.
The impact of missing continuous blood glucose samples on machine learning models for predicting postprandial hypoglycemia: An experimental analysis,
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Benchmarking ResNet for Short-Term Hypoglycemia Classification with DiaData
Refined DiaData with IQR outlier handling and Stineman interpolation enables ResNet to classify hypoglycemia onset up to 2 hours ahead, with 2-3% gain from data quality and 7% from more data.