Table 3.

Performance comparison of machine learning algorithms in each dataset from DKUH.

Model	Measure	Dataset
		Lab	Lab + ISNCSCI	Lab + ISNCSCI + K-MBI	Lab + ISNCSCI + K-MBI + FIM
GNN-GCN	Sensitivity	0.442 ± 0.143	0.367 ± 0.190	0.508 ± 0.107	0.494 ± 0.163
	Specificity	0.883 ± 0.034	0.886 ± 0.068	0.913 ± 0.043	0.960 ± 0.036
	Accuracy	0.808 ± 0.052	0.788 ± 0.041	0.837 ± 0.040	0.873 ± 0.040
	AUC	0.656 ± 0.077	0.626 ± 0.078	0.710 ± 0.058	0.727 ± 0.082
	F1-score	0.662 ± 0.084	0.622 ± 0.076	0.720 ± 0.064	0.754 ± 0.085
DNN	Sensitivity	0.420 ± 0.192	0.132 ± 0.101	0.472 ± 0.135	0.600 ± 0.129
	Specificity	0.903 ± 0.023	0.966 ± 0.031	0.920 ± 0.031	0.963 ± 0.035
	Accuracy	0.834 ± 0.040	0.810 ± 0.030	0.836 ± 0.034	0.895 ± 0.040
	AUC	0.647 ± 0.090	0.549 ± 0.053	0.696 ± 0.069	0.781 ± 0.069
	F1-score	0.662 ± 0.105	0.545 ± 0.076	0.707 ± 0.067	0.808 ± 0.071
SVM_linear	Sensitivity	0.106 ± 0.169	0.245 ± 0.160	0.560 ± 0.132	0.840 ± 0.110
	Specificity	0.898 ± 0.008	0.945 ± 0.035	0.893 ± 0.034	0.968 ± 0.026
	Accuracy	0.818 ± 0.015	0.813 ± 0.035	0.830 ± 0.039	0.944 ± 0.031
	AUC	0.532 ± 0.056	0.595 ± 0.077	0.727 ± 0.071	0.904 ± 0.058
	F1-score	0.502 ± 0.087	0.599 ± 0.104	0.723 ± 0.067	0.907 ± 0.052
SVM_RBF	Sensitivity	0.298 ± 0.144	0.278 ± 0.130	0.525 ± 0.139	0.492 ± 0.165
	Specificity	0.882 ± 0.024	0.935 ± 0.040	0.893 ± 0.040	0.930 ± 0.039
	Accuracy	0.798 ± 0.037	0.811 ± 0.037	0.824 ± 0.044	0.847 ± 0.043
	AUC	0.585 ± 0.062	0.606 ± 0.066	0.709 ± 0.075	0.711 ± 0.084
	F1-score	0.590 ± 0.077	0.619 ± 0.079	0.709 ± 0.072	0.723 ± 0.085
KNN	Sensitivity	0.208 ± 0.195	0.432 ± 0.148	0.282 ± 0.128	0.246 ± 0.127
	Specificity	0.894 ± 0.018	0.898 ± 0.059	0.893 ± 0.047	0.811 ± 0.043
	Accuracy	0.813 ± 0.031	0.810 ± 0.049	0.779 ± 0.044	0.811 ± 0.043
	AUC	0.559 ± 0.074	0.665 ± 0.074	0.588 ± 0.067	0.594 ± 0.067
	F1-score	0.551 ± 0.103	0.670 ± 0.074	0.593 ± 0.074	0.605 ± 0.086
Random Forest	Sensitivity	0.122 ± 0.131	0.262 ± 0.144	0.208 ± 0.133	0.073 ± 0.074
	Specificity	0.899 ± 0.008	0.933 ± 0.043	0.953 ± 0.042	0.990 ± 0.019
	Accuracy	0.820 ± 0.015	0.807 ± 0.030	0.813 ± 0.030	0.818 ± 0.021
	AUC	0.532 ± 0.040	0.597 ± 0.062	0.581 ± 0.058	0.532 ± 0.038
	F1-score	0.510 ± 0.068	0.602 ± 0.073	0.584 ± 0.074	0.511 ± 0.065
Logistic Regression	Sensitivity	0.380 ± 0.196	0.352 ± 0.153	0.438 ± 0.144	0.683 ± 0.163
	Specificity	0.907 ± 0.017	0.942 ± 0.040	0.918 ± 0.036	0.964 ± 0.029
	Accuracy	0.838 ± 0.031	0.831 ± 0.041	0.828 ± 0.036	0.911 ± 0.033
	AUC	0.630 ± 0.084	0.647 ± 0.077	0.678 ± 0.072	0.823 ± 0.078
	F1-score	0.643 ± 0.104	0.665 ± 0.083	0.689 ± 0.069	0.841 ± 0.065

Abbreviations: Lab = laboratory data; ISNCSCI = International Standards for Neurological Classification of Spinal Cord Injury; K-MBI = Korean version of the Modified Barthel Index; FIM = Functional Independence Measure.