Does Mike Cahill feel seen? The 41-year-old writer-director of science fiction has now made three films, each higher-profile than the last, about ways of seeing. This is literalized most literally in the second of these efforts, I Origins, which is also, not unrelatedly, the worst titled. Released in 2014, it's about vision scientists searching for the origin of the human eye--look, a pun--which, if you didn't know, is "the window," as one character literally says, "to the soul." They find it in the genes of a sightless worm, but not before Karen, played by Brit Marling, warns her lab partner that she, at least, has no interest in getting famous, in being seen: "Recognition makes me nauseous," she says.

Diabetes management is a difficult task for patients, who must monitor and control their blood glucose levels in order to avoid serious diabetic complications. It is a difficult task for physicians, who must manually interpret large volumes of blood glucose data to tailor therapy to the needs of each patient. 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 second provides an automated screen for excessive glycemic variability. The third aims to build a hypoglycemia predictor that could alert patients to dangerously low blood glucose levels in time to take preventive action. All are products of the 4 Diabetes Support SystemTM project, which uses AI to promote the health and wellbeing of people with type 1 diabetes. These emerging applications could potentially benefit 20 million patients who are at risk for devastating complications, thereby improving quality of life and reducing health care cost expenditures.

Diabetes management is a difficult task for patients, who must monitor and control their blood glucose levels in order to avoid serious diabetic complications. It is a difficult task for physicians, who must manually interpret large volumes of blood glucose data to tailor therapy to the needs of each patient. This paper describes three emerging applications that employ AI to ease this task and shares difficulties encountered in transitioning AI technology from university researchers to patients and physicians.