. 2021 Mar 26;50(7):20200611. doi: 10.1259/dmfr.20200611

Table 4.

peformance of learning modelsTable 4

Model (Origin of training and validating dataset)	Testing dataset	AUC	Cutoff value (%)	True positive(No. of condyles)	True negative(No. of condyles)	Accuracy (%)	Sensitivity (%)	Specificity (%)
Model A (Datatsets from hospital A)	Hospital A	0.85*	5.96	80/100	79/100	80.4	80.0	79.0
Model A (Datatsets from hospital A)	Hospital B	0.58*	99.94	60/100	58/100	59.0	60.0	58.0
Model B (Datasets from hospital B)	Hospital A	0.58^#	99.98	61/100	59/100	60.0	61.0	59.0
Model B (Datasets from hospital B)	Hospital B	0.86^#	56.23	80/100	82/100	81.0	80.0	82.0
Model AB (Combined datasets from hospitals A and B)	Hospital A	0.89	7.00	83/100	80/100	81.5	83.0	80.0
Model AB (Combined datasets from hospitals A and B)	Hospital B	0.91	36.00	85/100	84/100	84.5	85.0	84.0

AUC, Area under the curve receiver operating characteristic curve; CNN, Convolution Neural Network.

*,#: Statistically significant difference with p value < 0.05.