Academic Journal

Dilated Recurrent Neural Networks for Glucose Forecasting in Type 1 Diabetes

التفاصيل البيبلوغرافية
العنوان: Dilated Recurrent Neural Networks for Glucose Forecasting in Type 1 Diabetes
المؤلفون: Zhu, T, Li, K, Chen, J, Herrero, P, Georgiou, P
المصدر: Journal of Healthcare Informatics Research , 4 (3) pp. 308-324. (2020)
بيانات النشر: Springer Science and Business Media LLC
سنة النشر: 2020
المجموعة: University College London: UCL Discovery
مصطلحات موضوعية: Dilated recurrent neural network, Diabetes, Continuous glucose monitor (CGM), Glucose forecasting, Deep learning
الوصف: Diabetes is a chronic disease affecting 415 million people worldwide. People with type 1 diabetes mellitus (T1DM) need to self-administer insulin to maintain blood glucose (BG) levels in a normal range, which is usually a very challenging task. Developing a reliable glucose forecasting model would have a profound impact on diabetes management, since it could provide predictive glucose alarms or insulin suspension at low-glucose for hypoglycemia minimisation. Recently, deep learning has shown great potential in healthcare and medical research for diagnosis, forecasting and decision-making. In this work, we introduce a deep learning model based on a dilated recurrent neural network (DRNN) to provide 30-min forecasts of future glucose levels. Using dilation, the DRNN model gains a much larger receptive field in terms of neurons aiming at capturing long-term dependencies. A transfer learning technique is also applied to make use of the data from multiple subjects. The proposed approach outperforms existing glucose forecasting algorithms, including autoregressive models (ARX), support vector regression (SVR) and conventional neural networks for predicting glucose (NNPG) (e.g. RMSE = NNPG, 22.9 mg/dL; SVR, 21.7 mg/dL; ARX, 20.1 mg/dl; DRNN, 18.9 mg/dL on the OhioT1DM dataset). The results suggest that dilated connections can improve glucose forecasting performance efficiently.
نوع الوثيقة: article in journal/newspaper
وصف الملف: text
اللغة: English
Relation: https://discovery.ucl.ac.uk/id/eprint/10108768/1/Zhu2020_Article_DilatedRecurrentNeuralNetworks.pdf; https://discovery.ucl.ac.uk/id/eprint/10108768/
الاتاحة: https://discovery.ucl.ac.uk/id/eprint/10108768/1/Zhu2020_Article_DilatedRecurrentNeuralNetworks.pdf
https://discovery.ucl.ac.uk/id/eprint/10108768/
Rights: open
رقم الانضمام: edsbas.DFB75D0
قاعدة البيانات: BASE