Emerging Feature Extraction Techniques for Machine Learning-Based Classification of Carotid Artery Ultrasound Images

Table 4

Performance comparison of classification of carotid artery ultrasound images using ML approaches.

Algorithm	Accuracy	Specificity	Sensitivity	Precision	F score	AUC
Naive Bayes	82.82	88.11	76.1	83.44	79.60	85.77
DLVQ	91.68	98.51	83.01	97.77	89.78	98.14

DLVQ has recorded improved performance in terms of AUC, F score, precision, sensitivity, specificity, and accuracy compared with the Naive Bayes algorithm.