Study on the use of standard 12-lead ECG data for rhythm-type ECG classification problems.
Journal:
Computer methods and programs in biomedicine
Published Date:
Nov 10, 2021
Abstract
BACKGROUND AND OBJECTIVES: Most deep-learning-related methodologies for electrocardiogram (ECG) classification are focused on finding an optimal deep-learning architecture to improve classification performance. However, in this study, we proposed a methodology for fusion of various single-lead ECG data as training data in the single-lead ECG classification problem.