Scientists utilized plasma protein proteomics to identify proteins associated with the onset of type 1 diabetes.

Using advanced machine learning models, researchers in China were able to accurately predict incidence of gestational diabetes among pregnant women during their first trimester.

When Rosella took the risk-prediction algorithm that she and her team developed – the Diabetes Population Risk Tool – and applied it to Statistics Canada’s health information on the population, a ...

Machine learning has immense potential for improving diabetes care, particularly when used by diabetes care and education specialists.

A new study unveils a new, machine-learning derived model that can predict, with a high degree of accuracy, future heart failure among patients with diabetes.

We developed statistical and machine learning models to predict premature death from the presence of 17 chronic conditions and the patients’ age at diagnosis. We evaluated models using accuracy, ...

Trinity Life Sciences, a leader in advisory, insights and analytics for the life sciences industry, presented results from a ...

For example, by preventing hospitalizations in cases of just two widespread chronic illnesses — heart disease and diabetes — the United States could save billions of dollars a year.