Chicago researchers have been working on an algorithm, eCART, to decode cardiac arrest, the abrupt loss of heart function.

A new retrospective analysis leveraged the American College of Cardiology algorithm to score cardiac arrest arrivals and predict unfavorable neurological outcomes. It's now available on the internet.

Clinician-scientists have developed a clinical algorithm that, for the first time, distinguishes between treatable sudden cardiac arrest and untreatable forms of the condition.

The risk assessment algorithm consists of 13 clinical, electrocardiogram, and echocardiographic variables that could put a patient at higher risk of treatable sudden cardiac arrest.

A new artificial intelligence-based approach using scans of patients' hearts and their medical history can predict if they will die from cardiac arrest, a study published Thursday by Nature ...

Predictive Medical Technologies has developed a system that can mine the medical data of a patient—lab reports, monitors, nurse notes, etc.—and predict ...

Prediction is very difficult, especially if it’s about the future, Danish physicist Neil Bohr once said. And no health forecast has confounded doctors like sudden cardiac death.

Using neighborhood and local data in combination with existing information sources creates a more accurate prediction on a patient's recovery prospects after an out-of-hospital cardiac arrest ...

Sept. 4, 2003 (Vienna) — Patients who are successfully resuscitated after sudden cardiac arrest face about a 30% risk of recurrent events, but investigators for the Leiden Out of Hospital ...

A team of Johns Hopkins University biomedical engineers and Johns Hopkins Medicine heart specialists have developed an algorithm that warns doctors several hours before hospitalized COVID-19 patients ...