Electrical and Computer Engineering, University of Arizona, USA
*Corresponding author: Siteng Chen, Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA, Email: firstname.lastname@example.org
Submission: March 05, 2018; Published: April 03, 2018
ISSN : 2576-8816Volume4 Issue4
Arrhythmia classification with high precision is usually performed by cardiologists with high time consumption. Automatic arrhythmia classifiers based on artificial intelligence algorithm can help cardiologists to obtain better precision and reduce time consuming. In this mini-review, we compare optimization methods, machine learning methods and deep learning methods in cardiac arrhythmia classification. A high-performance classifier based on deep learning algorithm would be a viable direction of the future research.
Keywords: Cardia arrhythmia classification; Artificial intelligence; Machine learning; Deep learning; Convolutional neural network