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SOTA
Cancer-no cancer per image classification
Cancer No Cancer Per Image Classification On
Cancer No Cancer Per Image Classification On
Metrics
AUC
Results
Performance results of various models on this benchmark
Columns
Model Name
AUC
Paper Title
Multi-patch size DenseNet-121
0.809
Exploiting Patch Sizes and Resolutions for Multi-Scale Deep Learning in Mammogram Image Classification
SingleView_PatchBased_EfficientNet-B0
0.8033
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network
MorphHR-ResNet18_S896
0.7964
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
ResNet18_S896
0.7958
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
SingleView_PatchBased_EfficientNet-B3
0.7952
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network
Multi-resolution DenseNet-121
0.789
Exploiting Patch Sizes and Resolutions for Multi-Scale Deep Learning in Mammogram Image Classification
ResNet18_S448
0.7882
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
Feature Pyramid Network DenseNet-121
0.788
Exploiting Patch Sizes and Resolutions for Multi-Scale Deep Learning in Mammogram Image Classification
Patch-based DenseNet-121
0.784
Exploiting Patch Sizes and Resolutions for Multi-Scale Deep Learning in Mammogram Image Classification
MorphHR-ResNet18_S448
0.7836
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
MorphHR-ResNet18_S224
0.7523
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
VGG/ResNet
0.75
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network
VGG/ResNet
0.75
Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography
ResNet18_S224
0.7257
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
XGBoost
0.6849
Machine Learning Algorithms for Breast Cancer Detection in Mammography Images: A Comparative Study
VGG16
0.6822
Machine Learning Algorithms for Breast Cancer Detection in Mammography Images: A Comparative Study
0 of 16 row(s) selected.
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