. 2021 Oct 6;51(2):20210318. doi: 10.1259/dmfr.20210318

Table 1.

Accuracy values of the ML classifiers for the training and testing datasets and the studied feature extraction methods

ACCURACY	RADIOMIC FEATURES			p-value	SEMANTICS FEATURES			p-value	ASSOCIATED FEATURES			p-value
	KNN ^A SVM ^A MLP^A			Intra	KNN^A SVM^A MLP^A			Intra	KNN^A SVM^B MLP^C			Intra
	KNN ^A SVM ^A MLP^A			0.695	KNN^A SVM^A MLP^A			0.499	KNN^A SVM^B MLP^C			0.004
TRAINING	71.54% ^a	79.52% ^a	90.90% ^a	Inter	89.90% ^a	89.91% ^a	91.95% ^a	Inter	89% ^a	93.63% ^a	98.68% ^a	Inter
TESTING	68.08% ^a	76.59% ^a	63.82% ^a	0.296	87.23% ^a	95.74% ^a	91.48% ^a	0.758	82.97% ^b	87.23% ^b	91.49%^b	0.003

ANOVA test for repeated measures and post Tukey test.

Intra corresponds to KNN, SVM and MLP.

Inter corresponds to training and testing.

^dDifferent letters indicate statistically significant differences between groups.