A multimodal Transformer with cross-attention and multi-scale attention forecasts blood glucose from CGM and activity data, beating a CNN-LSTM baseline on AI-READI by about 10% in RMSE.
Deep multitask learning by stacked long short-term memory for predicting personalized blood glucose concentration,
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AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset
A multimodal Transformer with cross-attention and multi-scale attention forecasts blood glucose from CGM and activity data, beating a CNN-LSTM baseline on AI-READI by about 10% in RMSE.