A dual mode adaptive basal-bolus advisor based on reinforcement learning

no code implementations • 7 Jan 2019 • Qingnan Sun, Marko V. Jankovic, João Budzinski, Brett Moore, Peter Diem, Christoph Stettler, Stavroula G. Mougiakakou

Self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) are commonly used by type 1 diabetes (T1D) patients to measure glucose concentrations.

reinforcement-learning Reinforcement Learning (RL)

Predicting Blood Glucose with an LSTM and Bi-LSTM Based Deep Neural Network

no code implementations • 11 Sep 2018 • Qingnan Sun, Marko V. Jankovic, Lia Bally, Stavroula G. Mougiakakou

A deep learning network was used to predict future blood glucose levels, as this can permit diabetes patients to take action before imminent hyperglycaemia and hypoglycaemia.

Quantum Low Entropy based Associative Reasoning or QLEAR Learning

no code implementations • 30 May 2017 • Marko V. Jankovic

In other words, method is based on calculation of quantum entropy of the referent system and its relative change with the addition of the newly arrived sample.

Clustering General Classification