
AI spots hidden heart fat on standard ultrasounds
A new AI model extracts metabolic risk data directly from routine heart ultrasounds, bypassing the need for expensive CT scans.
Discover the newest research about AI innovations in 🤖 Machine Learning.

A new AI model extracts metabolic risk data directly from routine heart ultrasounds, bypassing the need for expensive CT scans.

Hospitals face a multi-million dollar dilemma: upgrade aging imaging hardware or accept degraded scan quality.

A new machine learning model proves we do not need expensive imaging or complex protein tracking to find patients whose knee pain will soon spike.

A new federal payment model is forcing digital health companies to prove their tools actually heal patients, not just log clinical hours.

A £30 million funding round reveals how private healthcare is bypassing broken public infrastructure to survive.

Automating insurance enrollment could solve one of medicine’s most expensive waiting games, but AI agents must first prove they can handle the regulatory minefield.

Deploying AI to halve diagnostic wait times is a massive win, but it risks creating a dangerous bottleneck further down the care pathway.

A new human-AI framework shows that the best way to clean up messy electronic health records is to let algorithms and doctors correct each other.

A new composite AI model can spot structural heart disease from a standard ECG before symptoms even appear, but its real value lies in predicting future risk.

A new machine learning model proves that how your blood pressure fluctuates over 24 hours is far more dangerous than a single high reading at the clinic.