An offline, point-of-care algorithm on a smartphone fundus camera generated disease-specific outputs without cloud connectivity, addressing a major deployment barrier in low-resource screening ...

For the first time, an Earth observation satellite has found what it was looking for — on its own, without human analysts on the ground. The milestone, which occurred in April, marks the first ...

You’re reading the web edition of STAT’s AI Prognosis newsletter, our subscriber-exclusive guide to artificial intelligence in health care and medicine. Sign up to get it delivered in your inbox every ...

We were unable to process your request. Please try again later. If you continue to have this issue please contact [email protected]. The Omnipod 6 automated insulin delivery algorithm met ...

Smoking, vaping, or using both products significantly increases the likelihood of developing prediabetes and diabetes, and the risk is even higher among Hispanic, Black, and low-income groups.

To this point, determination of genetic risk for Type 1 diabetes mostly has been limited to people with well-known and well-documented risk profiles. But with a machine learning tool created by ...

In people with type 1 diabetes (T1D), the immune system shuts down the body's ability to make the hormone insulin, responsible for regulating blood sugar and providing cells with glucose to produce ...

David Pogue is a six-time Emmy winner for his stories on "CBS Sunday Morning," where he's been a correspondent since 2002. Pogue hosts the CBS News podcast "Unsung Science." He's also a New York Times ...

We were unable to process your request. Please try again later. If you continue to have this issue please contact [email protected]. The 2026 update of AACE’s consensus statement algorithm ...

A University of Virginia Center for Diabetes Technology-developed algorithm – paired with a continuous glucose monitor – can help users better manage their type 2 diabetes by recommending insulin-dose ...

This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates Random Forest ...