title: Recognition of lead reversals in pediatric electrocardiograms.
abstract: We have trained artificial neural networks to detect right/left arm lead reversals in pediatric electrocardiograms with a performance significantly higher than that of currently used methods. We believe that this type of neural network can be a valuable type of quality control in pediatric electrocardiography.
authors.affiliation: Department of Clinical Physiology, Lund University, Sweden. lars.edenbrandt@klinfys.lu.se
authors.forename: L
authors.initials: L
authors.lastname: Edenbrandt
authors.forename: R
authors.initials: R
authors.lastname: Rittner
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002675:Child, Preschool; D003951:Diagnostic Errors / Q000517:prevention & control*; D004562:Electrocardiography / Q000295:instrumentation*; D004566:Electrodes; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D016571:Neural Networks, Computer; D010372:Pediatrics; D011787:Quality of Health Care