*Artificial Intelligence in Electrocardiogram for Classifying Arrhythmia: Review

Abstract

*Abstract: In recent years, artificial intelligence has been developing rapidly in terms of software algorithms such as machine learning, deep learning, reinforcement learning, and hardware implementations like IoT, embedded systems, and sensor network systems. Arrhythmia is a medical condition that occurs when the normal pumping mechanism of the human heart becomes irregular. Detecting arrhythmia types is one of the essential steps in diagnosing the condition, and it can help cardiologists make decisions. This paper summarizes the latest developments in artificial intelligence for electrocardiogram-based arrhythmia type classification problems. This review aims to keep track of new medical and computer science accomplishments in recent years. This study will also help understand the workspace available in cardiology with artificial intelligence and inspire naive researchers using the recent research findings. Furthermore, this paper presents a systematic review of artificial intelligence, data mining, machine learning, and deep learning with feature extraction methods for building the AI model for cardiological data.