A Dual Mode Adaptive Basal-Bolus Advisor Based on Reinforcement Learning

@article{Sun2018ADM,
  title={A Dual Mode Adaptive Basal-Bolus Advisor Based on Reinforcement Learning},
  author={Qingnan Sun and Marko V. Jankovic and Jo{\~a}o Budzinski and Brett L. Moore and Peter Diem and Christoph Stettler and Stavroula G. Mougiakakou},
  journal={IEEE Journal of Biomedical and Health Informatics},
  year={2018},
  volume={23},
  pages={2633-2641}
}
Self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) are commonly used by type 1 diabetes (T1D) patients to measure glucose concentrations. The proposed adaptive basal-bolus algorithm (ABBA) supports inputs from either SMBG or CGM devices to provide personalised suggestions for the daily basal rate and prandial insulin doses on the basis of the patients’ glucose level on the previous day. The ABBA is based on reinforcement learning, a type of artificial intelligence… CONTINUE READING
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