Deep Reinforcement Learning for Closed-Loop Blood Glucose Control

Understand

People with type 1 diabetes (T1D) lack the ability to produce the insulin their bodies need.

• As a result, they must continually make decisions about how much insulin to self-administer to adequately control their blood glucose levels.
• Longitudinal data streams captured from wearables, like continuous glucose monitors, can help these individuals manage their health, but currently the majority of the decision burden remains on the user.
• To relieve this burden, researchers are working on closed-loop solutions that combine a continuous glucose monitor and an insulin pump with a control algorithm in an `artificial pancreas.' Such systems aim to estimate and deliver the appropriate amount of insulin.