Application of deep learning and feature selection technique on external root resorption identification on CBCT images

Reduwan, Nor Hidayah; Abdul Aziz, Azwatee Abdul; Mohd Razi, Roziana; Abdullah, Erma Rahayu Mohd Faizal; Mazloom Nezhad, Seyed Matin; Gohain, Meghna; Ibrahim, Norliza

doi:10.1186/s12903-024-03910-w

Table 6 Dunn’s post-hoc test between models

From: Application of deep learning and feature selection technique on external root resorption identification on CBCT images

Sample 1- Sample 2	Test Statistic	Std. Error	Std. Test Statistic	Sig.	Adj. Sig. a
RF + EFNET-FS + RF + EFNET	-2.500	8.065	-0.310	0.757	1.000
RF + EFNET-SVM + EFNET	-7.250	8.065	-0.899	0.369	1.000
RF + EFNET-FS + SVM + EFNET	-12.583	8.065	-1.560	0.119	1.000
RF + EFNET-SVM + VGG	-16.000	8.065	-1.984	0.047	1.000
RF + EFNET-RF + VGG	19.417	8.065	2.408	0.016	0.450
RF + EFNET-FS + SVM + VGG	-21.667	8.065	-2.687	0.007	0.202
RF + EFNET-FS + RF + VGG	-26.583	8.065	-3.296	0.001	0.027*
FS + RF + EFNET-SVM + EFNET	4.750	8.065	0.589	0.556	1.000
FS + RF + EFNET-FS + SVM + EFNET	-10.083	8.065	-1.250	0.211	1.000
FS + RF + EFNET-SVM + VGG	13.500	8.065	1.674	0.094	1.000
FS + RF + EFNET-RF + VGG	16.917	8.065	2.098	0.036	1.000
FS + RF + EFNET-FS + SVM + VGG	-19.167	8.065	-2.377	0.017	0.489
FS + RF + EFNET-FS + RF + VGG	24.083	8.065	2.986	0.003	0.079
SVM + EFNET-FS + SVM + EFNET	-5.333	8.065	-0.661	0.508	1.000
SVM + EFNET-SVM + VGG	8.750	8.065	1.085	0.278	1.000
SVM + EFNET-RF + VGG	12.167	8.065	1.509	0.131	1.000
SVM + EFNET-FS + SVM + VGG	-14.417	8.065	-1.788	0.074	1.000
SVM + EFNET-FS + RF + VGG	-19.333	8.065	-2.397	0.017	0.463
FS + SVM + EFNET-SVM + VGG	3.417	8.065	0.424	0.672	1.000
FS + SVM + EFNET-RF + VGG	6.833	8.065	0.847	0.397	1.000
FS + SVM + EFNET-FS + SVM + VGG	9.083	8.065	1.126	0.26	1.000
FS + SVM + EFNET-FS + RF + VGG	14.000	8.065	1.736	0.083	1.000
SVM + VGG-RF + VGG	3.417	8.065	0.424	0.672	1.000
SVM + VGG-FS + SVM + VGG	-5.667	8.065	-0.703	0.482	1.000
SVM + VGG-FS + RF + VGG	-10.583	8.065	-1.312	0.189	1.000
RF + VGG-FS + SVM + VGG	-2.250	8.065	-0.279	0.78	1.000
RF + VGG-FS + RF + VGG	-7.167	8.065	-0.889	0.374	1.000
FS + SVM + VGG-FS + RF + VGG	4.917	8.065	0.610	0.542	1.000

Each row tests the null hypothesis that the Sample 1 and Sample 2 distributions are the same
Asymptotic significances (2-sided tests) are displayed. The significance level is 0.050
a Significance values have been adjusted by the Bonferroni correction for multiple tests
^*Significant different p < 0.05

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ISSN: 1472-6831

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