Glucose Forecasting and Hypoglycemia Forewarning in Type 1 and Type 2 Diabetes using Deep Learning

Introduction

This is the official implementation of:

Glucose forecasting and hypoglycemia forewarning in type 1 and type 2 diabetes using deep learning

Source code: DL_BGPred-main.zip

Publicly Available Diabetes Dataset

This repository also archives publicly available datasets for type 1 and type 2 diabetes for convenience. Please cite the original sources when using these data. Details of these datasets are shown in Table 1.

Table 1. Dataset Information

References

[1] Marling, C., and Bunescu, R. (2020). The OhioT1DM dataset for blood glucose level prediction: Update 2020. CEUR Workshop Proc. 2675, 71–74.

[2] Lum, J.W., Bailey, R.J., Barnes-Lomen, V., Naranjo, D., Hood, K.K., Lal, R.A., Arbiter, B., Brown, A.S., DeSalvo, D.J., Pettus, J., et al. (2021). A real-world prospective study of the safety and effectiveness of the loop open source automated insulin delivery system. Diabetes Technol. Ther. 23, 367–375.

[3] JDRF CGM Study Group (2008). JDRF randomized clinical trial to assess the efficacy of real-time continuous glucose monitoring in the management of type 1 diabetes: Research design and methods. Diabetes Technol. Ther. 10, 310–321.

[4] Aleppo, G., Ruedy, K.J., Riddlesworth, T.D., Kruger, D.F., Peters, A.L., Hirsch, I., Bergenstal, R.M., Toschi, E., Ahmann, A.J., Shah, V.N., et al. (2017). REPLACE-BG: A randomized trial comparing continuous glucose monitoring with and without routine blood glucose monitoring in adults with well-controlled type 1 diabetes. Diabetes Care 40, 538–545.

[5] Zhao, Q., Zhu, J., Shen, X., Lin, C., Zhang, Y., Liang, Y., Cao, B., Li, J., Liu, X., Rao, W., et al. (2023). Chinese diabetes datasets for data-driven machine learning. Sci. Data 10, 35.

[6] Colas, A., Vigil, L., Vargas, B., Cuesta-Frau, D., and Varela, M. (2019). Detrended fluctuation analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics. PLOS One 14, e0225817.