Young Adults

A 12-Lead ECG-Based System With Physiological Parameters and Machine Learning to Identify Right Ventricular Hypertrophy in Young Adults
Author(s)3: Gen-Min Lin, Henry Horng-Shing Lu
A 12-Lead ECG-Based System With Physiological Parameters and Machine Learning to Identify Right Ventricular Hypertrophy in Young Adults 675 601 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

The presence of right ventricular hypertrophy (RVH) accounts for approximately 5-10% in young adults. The sensitivity estimated by commonly used 12-lead electrocardiographic (ECG) criteria for identifying the presence of RVH…

read more

An Electrocardiographic System with Anthropometrics via Machine Learning to Screen Left Ventricular Hypertrophy among Young Adults
Author(s)3: Gen-Min Lin, Kiang Liu
An Electrocardiographic System with Anthropometrics via Machine Learning to Screen Left Ventricular Hypertrophy among Young Adults 908 575 IEEE Journal of Translational Engineering in Health and Medicine (JTEHM)

The prevalence of physiological and pathological left ventricular hypertrophy (LVH) among young adults is about 5%. A use of electrocardiographic (ECG) voltage criteria and machine learning for the ECG parameters…

read more
Search this website