Lumiata, a healthcare analytics company, said it will launch a tool called Risk Matrix that takes a patient's electronics record, combines it with artificial intelligence and risk algorithms to predict health over time for people with chronic conditions. The software, designed for insurers and healthcare providers, is designed to analyze models based on 175 million patient record years and provide clinical rationale for each prediction. Risk Matrix provides real-time predictions for more than 20 major diseases including congestive heart failure and diabetes. Insurers and companies are offering programs for chronic conditions, but often identify too many people as risks.

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.