A comparative study of heterogeneous machine learning algorithms for arrhythmia classification using feature selection technique and multi-dimensional datasets

• Published in: Engineering Research Express Vol. 6; no. 3; pp. 35209 - 35229
• Main Authors: Sharma, Abhinav, Dhanka, Sanjay, Kumar, Ankur, Maini, Surita
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.09.2024
• Subjects: arrhythmia; artificial intelligence; extreme gradient boosting (XGB); logistic regression (LG); machine learning; random forest (RF)

Arrhythmia, a common cardiovascular disorder, refers to the abnormal electrical activity within the heart, leading to irregular heart rhythms. This condition affects millions of people worldwide, with severe implications on cardiac function and overall health. Arrhythmias can strike anyone at any ag...