In a recent study published in BMC Medicine, researchers identified diabetic individuals among populations with normal fasting glucose using common physical examination indexes via machine ...

The performance of different machine learning models in detecting hepatitis among people with diabetes.

This overview examines the integration of machine learning (ML) approaches into diabetes prediction and diagnosis, highlighting the evolution from classical statistical methods to advanced data ...

Automated machine-learning models accurately identified risk for diabetic retinopathy progression using ultra-widefield retinal images, according to a study published in JAMA Ophthalmology.

The risk for poor glycemic control in patients with type 2 diabetes can be predicted with confidence by using machine learning methods, a new study finds. The most important factors predicting ...

The same type of machine learning methods used to pilot self-driving cars and beat top chess players could help type-1 diabetes sufferers keep their blood glucose levels in a safe range.

An automated insulin delivery system controlled by an artificial intelligence machine learning model may perform just as well as a system using a traditional equation-based insulin dosing ...

The same type of machine learning methods used to pilot self-driving cars and beat top chess players could help type-1 diabetes sufferers keep their blood glucose levels in a safe range.

Children's Mercy Kansas City (Mo.) and Boston-based Joslin Diabetes Center will deploy predictive models for Type 1 diabetes management using technology from Cambridge, Mass.-based Cyft.

Researchers from Edith Cowan University (ECU) are developing an artificial intelligence algorithm that can use bone density ...

This overview examines the integration of machine learning (ML) approaches into diabetes prediction and diagnosis, highlighting the evolution from classical statistical methods to advanced data ...