Table 9:

Performance comparison between FLocK-based classifiers M_FLocK and CNN approaches, AlexNet M_Alex and ResNet M_Res, for (a) OP-SCC HPV status classification and (b) prognosis of ES-NSCLC use cases. For the results on the training set O_train and L_train, we reported the mean AUC under 3-fold CV for the OP-SCC use case and the mean AUC under 10-fold CV for the ES-NSCLC use case.

OP-SCC HPV Status Classification
Classifier	Cohort	AUC	Accuracy	Specificity	Sensitivity
MAlex	Otrain	0.79±0.05	0.78±0.04	0.82±0.09	0.74±0.09
MAlex	Otest	0.78	0.77	0.72	0.80
MRes	Otrain	0.82±0.04	0.80±0.03	0.86±0.09	0.72±0.08
MRes	Otest	0.81	0.80	0.75	0.84
MFLocK	Otrain	0.80±0.04	0.77±0.03	0.83±0.09	0.71±0.08
MFLocK	Otest	0.76	0.80	0.63	0.95
MFLocK+COrE	Otest	0.84	0.85	0.82	0.88
ES-NSCLC Prognosis
Classifier	Cohort	AUC	Accuracy	Specificity	Sensitivity
MAlex	Ltrain	0.55±0.04	0.54±0.04	0.57±0.13	0.53±0.15
MAlex	Ltest	0.56	0.57	0.55	0.58
MRes	Ltrain	0.56±0.03	0.55±0.04	0.58±0.12	0.54±0.13
MRes	Ltest	0.56	0.55	0.54	0.57
MFLocK	Ltrain	0.68±0.03	0.67±0.06	0.71±0.10	0.65±0.09
MFLocK	Ltest	0.70	0.72	0.70	0.75