IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Genetic algorithm based NARX model identification for evaluation of insulin sensitivity
Applied Soft Computing
Diagnosing diabetes using neural networks on small mobile devices
Expert Systems with Applications: An International Journal
Journal of Electrical and Computer Engineering - Special issue on Electrical and Computer Technology for Effective Diabetes Management and Treatment
Artificial neural networks for closed loop control of in silico and ad hoc type 1 diabetes
Computer Methods and Programs in Biomedicine
Modelling irregular samples for analyzing the risk of complications of diabetes mellitus
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
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We study the application of neural networks to modeling the blood glucose metabolism of a diabetic. In particular we consider recurrent neural networks and time series convolution neural networks which we compare to linear models and to nonlinear compartment models. We include a linear error model to take into account the uncertainty in the system and for handling missing blood glucose observations. Our results indicate that best performance can be achieved by the combination of the recurrent neural network and the linear error model