An international group of researchers developed a deep learning model capable of identifying accessory pathways in patients with Wolff-Parkinson-White syndrome.

Tempus, a Chicago-based healthcare technology company, collaborated with Geisinger on the solution.

The new study, published in JAMA Cardiology, included more than 800 hypertension patients aged 75 years or older. 

The team's deep neural network was trained on more than 1.6 million 12-lead ECGs. 

The clearance includes multiple algorithms capable of identifying key findings in a 30-second ECG.

The study, published in Circulation: Arrhythmia and Electrophysiology, included data from more than 1,600 patients who presented at the ED with shortness of breath. 

A new wearable necklace can be used to detect atrial fibrillation (AFib), according to new findings published through the European Society of Cardiology’s EHRA Essentials 4 You platform.

A simple ECG score could help physicians estimate infarct size in patients with prior MI, according to work published Jan. 24 in the Journal of the American Heart Association.