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    A hybrid Transformer-LSTM model apply to glucose prediction by Bian, QingXiang, As’arry, Azizan, Cong, XiangGuo, Md Rezali, Khairil Anas

    Published 2024
    “…This dataset includes historical glucose readings and equipment calibration values, making it highly suitable for developing predictive models due to its richness and real-time applicability. Our findings demonstrate that the hybrid Transformer-LSTM model significantly outperforms the standard LSTM model, achieving Mean Square Error (MSE) values of 1.18, 1.70, and 2.00 at forecasting intervals of 15, 30, and 45 minutes, respectively. …”
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