DeepVAQ : an adaptive deep learning for prediction of vascular access quality in hemodialysis patients

Table 8 A comparison of prediction results of models

Models	Accuracy	Sensitivity	Specificity	Precision	F-Score
Decision Tree [34]	0.2531	0.1563	0.6550	0.0679	0.3051
Naive Bayes [35]	0.5816	0.3041	0.7159	0.4348	0.2489
k-Nearest-Neighbours (kNN) [37]	0.4735	0.2492	0.6912	0.3237	0.1230
DeepVAQ model (A proposed model)	0.9213^a	0.8431^a	0.9614^a	0.8762^a	0.8364^a

ISSN: 1472-6947