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Review
. 2018 Feb 4:2018:2016282.
doi: 10.1155/2018/2016282. eCollection 2018.

Automated Diagnosis of Coronary Artery Disease: A Review and Workflow

Qurat-Ul-Ain Mastoi  1 , Teh Ying Wah  1 , Ram Gopal Raj  1 , Uzair Iqbal  1
Affiliations
Review

Automated Diagnosis of Coronary Artery Disease: A Review and Workflow

Qurat-Ul-Ain Mastoi et al. Cardiol Res Pract. .

Abstract

Coronary artery disease (CAD) is the most dangerous heart disease which may lead to sudden cardiac death. However, CAD diagnoses are quite expensive and time-consuming procedures which a patient need to go through. The aim of our paper is to present a unique review of state-of-the-art methods up to 2017 for automatic CAD classification. The protocol of review methods is identifying best methods and classifier for CAD identification. The study proposes two workflows based on two parameter sets for instances A and B. It is necessary to follow the proper procedure, for future evaluation process of automatic diagnosis of CAD. The initial two stages of the parameter set A workflow are preprocessing and feature extraction. Subsequently, stages (feature selection and classification) are same for both workflows. In literature, the SVM classifier represents a promising approach for CAD classification. Moreover, the limitation leads to extract proper features from noninvasive signals.

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Figures

Figure 1
Figure 1
Workflow for parameter set A.
Figure 2
Figure 2
Workflow for parameter set B.
Figure 3
Figure 3
State-of-the-art classifiers.
See this image and copyright information in PMC

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