HAHNet: a convolutional neural network for HER2 status classification of breast cancer

BMC Bioinformatics

Table 1 This table presents the performance evaluation results of all models in the comparative experiment

Model	Accuracy	Precision	Recall	F-score	MCC	AUC
HAHNet	0.9365	0.9367	0.9246	0.9366	0.9041	0.99
HE-HER2Net	0.8701	0.8773	0.8700	0.8711	0.8076	0.91
InceptionV3	0.8423	0.8448	0.8101	0.8428	0.7629	0.88
DenseNet161	0.8096	0.8156	0.7964	0.8112	0.7159	0.87
DenseNet201	0.7656	0.7686	0.7556	0.7667	0.6484	0.84
ResNet101	0.7277	0.7280	0.7221	0.7276	0.5898	0.82
ResNet152	0.6899	0.6852	0.6342	0.6832	0.5231	0.79
AlexNet	0.6949	0.7089	0.7211	0.6981	0.5524	0.80
Vgg19	0.6653	0.6741	0.5785	0.6621	0.4894	0.72

ISSN: 1471-2105