Machine Learning Approach for Diagnosis and Prognosis of Cardiac Arrhythmia Condition Using a Minimum Feature Set and Auto-Segmentation-Based Window Optimisation
Cardiovascular diseases have become extremely prevalent in the global population. Several accurate classification methods for arrhythmias have been proposed in the healthcare literature. However, extensive research is required to improve the prediction accuracy of various arrhythmia conditions. In t...
Main Authors: | Swetha Rameshbabu, Sabitha Ramakrishnan |
---|---|
Format: | Article |
Language: | English |
Published: |
Kaunas University of Technology
2023-10-01
|
Series: | Elektronika ir Elektrotechnika |
Subjects: | |
Online Access: | https://eejournal.ktu.lt/index.php/elt/article/view/34357 |
Similar Items
-
A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks
by: Jindong Tan, et al.
Published: (2012-09-01) -
Finite state Markovian decision processes /
by: 229752 Derman, Cyrus
Published: (1970) -
Simulation-based algorithms for Markov decision processes /
by: Chang, Hyeong Soo
Published: (2007) -
Uncertainty-Aware Deep Learning-Based Cardiac Arrhythmias Classification Model of Electrocardiogram Signals
by: Ahmad O. Aseeri
Published: (2021-06-01) -
Development and optimisation of three-dimensional freeze-dried collagen-based scaffolds
by: Xue, B, et al.
Published: (2014)