February 1, 2021
View Full PaperArtificial Intelligence–Enabled Assessment of the Heart Rate Corrected QT Interval Using a Mobile Electrocardiogram Device
Structured PICO
Does an AI deep neural network using a mobile ECG device accurately predict the QTc compared to a standard 12-lead ECG?
I
Intervention
AI deep neural network (DNN) using smartphone-enabled electrodes (mobile ECG device)
C
Comparator
Standard 12-lead ECG
O
Outcome
Prediction of the heart rate corrected QT interval (QTc)surrogate
An AI-enabled mobile ECG device can accurately estimate QTc, offering a potential cost-effective screening tool for long QT syndrome when standard 12-lead ECG is unavailable.
Abstract
Using smartphone-enabled electrodes, an AI DNN can predict accurately the QTc of a standard 12-lead ECG. QTc estimation from an AI-enabled mECG device may provide a cost-effective means of screening for both acquired and congenital long QT syndrome in a variety of clinical settings where standard 12-lead electrocardiography is not accessible or cost-effective.