Diabetes App Forecasts Blood Sugar Levels
New York, NY (April 27, 2017)—Columbia University researchers have developed a personalized algorithm that predicts the impact of particular foods on an individual’s blood sugar levels. The algorithm has been integrated into an app, Glucoracle, that will allow individuals with type 2 diabetes to keep a tighter rein on their glucose levels—the key to preventing or controlling the major complications of a disease that affects 8 percent of Americans.
The findings were published online today in PLoS Computational Biology.
Medications are often prescribed to help patients with type 2 diabetes manage their blood sugar levels, but exercise and diet also play an important role.
“While we know the general effect of different types of food on blood glucose, the detailed effects can vary widely from one person to another and for the same person over time,” said lead author David Albers, PhD, associate research scientist in biomedical informatics at Columbia University Medical Center (CUMC). “Even with expert guidance, it’s difficult for people to understand the true impact of their dietary choices, particularly on a meal-to-meal basis. Our algorithm, integrated into an easy-to-use app, predicts the consequences of eating a specific meal before the food is eaten, allowing individuals to make better nutritional choices during mealtime.”
The algorithm uses a technique called data assimilation, in which a mathematical model of a person’s response to glucose is regularly updated with observational data—blood sugar measurements and nutritional information—to improve th