A team at UCSF developed a multitask deep learning framework that can effectively predict Alzheimer’s disease diagnosis, cognitive scores, and future cognitive decline using only baseline MRI and ...

The AI machine learning model to detect a disorder that typically affects babies who are born early was developed by a team of University of Rochester researchers.

Artificial intelligence shows promise for improving care for peripheral artery disease through earlier detection, improved ...

A model made using machine learning can predict if CPAP use in patients with obstructive sleep apnea will benefit or harm ...

Artificial intelligence (AI) refers to computer systems designed to perform tasks that require human intelligence, while machine learning (ML) is used to learn patterns from data and subsequently ...

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...

In a recent study published in the journal Communications Medicine, a group of researchers developed and validated scalable machine learning models that predict 12-month Mini-Mental State Examination ...

Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer’s disease with nearly 93% accuracy.

A Yale research team has created a new imaging technique that reveals the hidden connections between aging, disease, and genetic activity in human cells. Using a novel machine learning approach, the ...

A tool developed by the American Heart Association (AHA), proven to accurately predict heart disease risk for Americans, can ...