Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs

Sex and age have long been known to affect the ECG. Several biologic variables and anatomic factors may contribute to sex and age-related differences on the ECG. We hypothesized that a convolutional neural network (CNN) could be trained through a process called deep learning to predict a person'...

Full description

Saved in:

Bibliographic Details
Published in:	Circulation. Arrhythmia and electrophysiology Vol. 12; no. 9; p. e007284
Main Authors:	Attia, Zachi I, Friedman, Paul A, Noseworthy, Peter A, Lopez-Jimenez, Francisco, Ladewig, Dorothy J, Satam, Gaurav, Pellikka, Patricia A, Munger, Thomas M, Asirvatham, Samuel J, Scott, Christopher G, Carter, Rickey E, Kapa, Suraj
Format:	Journal Article
Language:	English
Published:	United States 01.09.2019
Subjects:	Adolescent Adult Aged Algorithms Artificial Intelligence Deep Learning Electrocardiography - methods Female Humans Male Middle Aged Neural Networks, Computer Retrospective Studies Young Adult coronary disease hypertension neural network artificial intelligence electrocardiography
ISSN:	1941-3084, 1941-3084
Online Access:	Get more information
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!