An AI platform designed to quickly read an x-ray and determine the manufacturer and model of a cardiac rhythm device may quicken treatment in the event of device failure, according to a study published in JACC: Clinical Electrophysiology.
Lead author James P. Howard, MB BChir, National Heart and Lung Institute, Imperial College London, and colleagues reported a convolutional neural network (CNN) identified the manufacturer from an x-ray with 99.6 percent accuracy. The method beat five cardiologists in identifying images of 1,676 devices, including 45 models from five manufacturers.
All the algorithm needs is for the user to upload an x-ray image of the device to a computer containing the software. Currently, it can only identify the 45 devices it has been trained to pick out, but it may already have important clinical implications.
“Pacemaker programmers are portable but bulky, and only the manufacturer, the specific programmer, would be able to communicate with the patient’s device,” Howard and colleagues wrote. “Knowing which programmer to bring saves valuable clinical time. Not only may this facilitate rapid interrogation of a device in an emergency, but also the provision of emergency treatment, such as the delivery of anti-tachycardia pacing in a patient presenting with ventricular tachycardia.”
Read the entire story in CardiovascularBusiness below.