Table 3.

Tukey post hoc contrast analysis of predicted marginal mean difference (SE) between algorithms by image type

Image type	Contrast	Marginal mean difference (SE)	Z ratio	Adjusted P-value
Color	CNN1 – CNN with weights	−0.7573 (0.215)	0.0153	0.0153
Color	CNN – Ensemble	−0.6719 (0.209)	−3.211	0.0433
Color	CNN – ResNET2	0.3505 (0.174)	2.017	0.5871
Color	CNN – ResNET with weight	−0.0801 (0.186)	−0.429	1
Color	CNN with weights – Ensemble	0.0854 (0.237)	0.361	1
Color	CNN with weights – ResNET	1.1078 (0.206)	5.37	<0.0001
Color	CNN with weights – ResNET with weight	0.6773 (0.217)	3.122	0.0566
Color	Ensemble – ResNET	1.0224 (0.201)	5.095	<0.0001
Color	Ensemble – ResNET with weight	0.5919 (0.212)	2.798	0.137
Color	ResNET – ResNET with weight	−0.4305 (0.177)	−2.437	0.3036
Grayscale	(CNN) – (Ensemble)	−0.4688 (0.175)	−2.687	0.1789
Grayscale	(CNN) – (ResNET)	0.2886 (0.145)	1.996	0.602
Grayscale	(CNN) – (ResNET with weight)	−0.0423 (0.155)	−0.272	1
Grayscale	(CNN with weights) – (Ensemble)	−0.3269 (0.183)	−1.782	0.7468
Grayscale	(CNN with weights) – (ResNET)	0.4306 (0.155)	2.769	0.147
Grayscale	(CNN with weights) – (ResNET with weight)	0.0997 (0.166)	0.602	0.9999
Grayscale	(Ensemble) – (ResNET)	0.7575 (0.171)	4.422	0.0004
Grayscale	(Ensemble) – (ResNET with weight)	0.4266 (0.180)	2.364	0.3477

¹CNN, convolutional neural network.

²ResNET, residual network.