A powerful new real-world data platform could transform how scientists predict and understand Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD), reports a new study at Columbia ...

We present one of the first comprehensive evaluations of predictive information derived from retinal fundus photographs, illustrating the potential and limitations of readily accessible and low-cost ...

Researchers developed a scalable framework that predicts insulin resistance using wearable-device signals, routine blood biomarkers, and demographic data, with stronger performance when these data ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

In A Nutshell Researchers used a machine learning model to rank all 50 U.S. states and Washington, D.C. by socioeconomic vulnerability to flu-like illness, finding wide regional variation in risk.

Diabetes affects over 537 million adults globally, with early detection critical for effective treatment and management. This project develops a machine learning classification model to predict ...

It’s everywhere, as the author learned the hard way while making as little contact as possible with machine learning and generative artificial intelligence. It’s everywhere, as the author learned the ...

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...