Emerging Applications for Intelligent Diabetes Management

Marling, Cindy (Ohio University) | Wiley, Matthew (University of California, Riverside) | Bunescu, Razvan (Ohio University) | Shubrook, Jay (Ohion University) | Schwartz, Frank (Ohio University)

AI Magazine 

Diabetes management is a difficult task for patients, who must monitor and control their blood glucose levels in order to avoid serious diabetic complications. This paper describes three emerging applications that employ AI to ease this task: (1) case-based decision support for diabetes management; (2) machine learning classification of blood glucose plots; and (3) support vector regression for blood glucose prediction. The first application provides decision support by detecting blood glucose control problems and recommending therapeutic adjustments to correct them. The third aims to build a hypoglycemia predictor that could alert patients to dangerously low blood glucose levels in time to take preventive action.