
Remote blood pressure monitoring leaves minority gaps
Giving patients Bluetooth blood pressure cuffs improves overall health outcomes, but technology alone cannot erase deep-seated racial disparities in clinical care.
Discover the newest research about AI innovations in 🫀 Cardiology.

Giving patients Bluetooth blood pressure cuffs improves overall health outcomes, but technology alone cannot erase deep-seated racial disparities in clinical care.

By measuring what an artificial intelligence model fails to reconstruct in an electrocardiogram, researchers have found a highly generalizable way to predict mortality.

A new pilot study suggests heart failure patients can safely adjust their own daily diuretic doses using AI-guided sensor readings, shifting the burden away from overloaded clinical teams.

A routine ten-second heart trace holds hidden clues to chronic diseases far beyond the cardiovascular system.

Your calendar age says you are fifty, but a quick heart scan might prove your cardiovascular system is already running on borrowed time.

A new machine learning method extracts high-quality heart disease risk data from low-dose scans that doctors usually ignore for calcium scoring.

A new digital twin model shows that one-third of heart failure patients fail cardiac therapy because surgeons are aiming at the wrong target.

A new deep learning model spots chronic kidney disease using routine heart ultrasounds, bypassing the need for immediate blood work.

A new foundation model shows that overnight pulse oximetry data contains deep physiological signatures that can predict future hypertension and next-day blood sugar levels.

Automated medical registries promise to slash administrative burdens, but a new trial reveals that large language models are not yet reliable enough to replace human chart reviewers.