Nature

A distributional reinforcement learning model for optimal glucose control after cardiac surgery

This study introduces Glucose Level Understanding and Control Optimized for Safety and Efficacy (GLUCOSE), a distributional offline reinforcement learning algorithm for optimizing insulin dosing after ...
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A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data

CGMformer is first self-supervised pretrained on CGM data to gain fundamental knowledge of the glucose dynamics, and then applied to a multitude of downstream clinical applications. The extractable ...
Nature

Non-invasively accuracy enhanced blood glucose sensor using shallow dense neural networks with NIR monitoring and medical features

Non-invasive and accurate method for continuous blood glucose monitoring, the self-testing of blood glucose is in quest for better diagnosis, control and the management of diabetes mellitus (DM).