title: Using a neural network to diagnose the hypertrophic portions of hypertrophic cardiomyopathy.
abstract: We studied the ability of a neural network to identify the hypertrophic cardiac regions in hypertrophic cardiomyopathy, with the network using electrocardiographic (ECG) information alone. Computer-based electrocardiography remains a fundamental diagnostic method for analysis of cardiac contour and rhythm. Almost all patients with hypertrophic cardiomyopathy have some abnormal findings on electrocardiography, but it is very difficult, even for an experienced cardiologist, to identify the hypertrophic regions on the basis of electrocardiography alone. Since neural networks are known to be better at pattern recognition than humans are, we tried using a neural network trained with ECG information to identify the hypertrophic regions in hypertrophic cardiomyopathy.
authors.affiliation: Department of Medical Information and Medical Records, Nagoya University Hospital, Japan.
authors.forename: N
authors.initials: N
authors.lastname: Ouyang
authors.forename: K
authors.initials: K
authors.lastname: Yamauchi
mesh_terms: D000465:Algorithms; D002312:Cardiomyopathy, Hypertrophic / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted; D004452:Echocardiography; D004562:Electrocardiography; D006801:Humans; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests