The team plans to further test the new model on more patients and expand the new algorithm to use with other types of heart ...

A new AI algorithm is nearly twice as accurate as physicians at forecasting a sudden cardiac arrest in people with ...

The research, led by Johns Hopkins University and funded by the federal government, focuses on hypertrophic cardiomyopathy, a ...

"Supported by MAARS, clinicians can deliver personalized care to their patients and protect them appropriately from SCDA ...

A new AI model is much better than doctors at identifying patients likely to experience cardiac arrest. The linchpin is the ...

Right ventricular (RV) strain by cardiac magnetic resonance imaging (MRI) has been reported to yield robust prognostic data ...

An advanced Johns Hopkins AI model called MAARS combs through underused heart MRI scans and complete medical records to spot hidden scar patterns that signal sudden cardiac death, dramatically ...

Multimodal AI for ventricular Arrhythmia Risk Stratification (MAARS), predicts individual patients' risk for sudden cardiac ...

From detecting cancer and remote patient monitoring to streamlined documentation and automated prior authorizations, here are 15 proven clinical uses of AI — with results: ...

An experimental method, which can predict the aging rate of both brain and body, may detect who should implement lifestyle changes to reduce their risk of age-related conditions, including dementia.

Artificial intelligence (AI)–based electrocardiogram interpretation (AI-ECG) detected left ventricular systolic dysfunction ...