An Interpretable Hand-Crafted Feature-Based Model for Atrial Fibrillation Detection

An Interpretable Hand-Crafted Feature-Based Model for Atrial Fibrillation Detection

Atrial Fibrillation (AF) is the most common type of cardiac arrhythmia. Early diagnosis of AF helps to improve therapy and prognosis. Machine Learning (ML) has been successfully applied to improve the effectiveness of Computer-Aided Diagnosis (CADx) systems for AF detection. Presenting an explanatio...

Full description

Bibliographic Details
Main Authors: Rahimeh Rouhi, Marianne Clausel, Julien Oster, Fabien Lauer
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-05-01
Series:Frontiers in Physiology
Subjects:
atrial fibrillation
feature importance
interpretability
feature selection
classification
computer-aided diagnosis
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2021.657304/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2021.657304/full

Similar Items