NASLung (ours)

Reported on 5 benchmarks across 3 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology4 results

Neural Architecture SearchonLIDC-IDRI
F1 score· 2021-01-19
0.8929
SOTA
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification arXiv:2101.07429
Neural Architecture SearchonLIDC-IDRI
Specificity (VEB+)· 2021-01-19
95.04
SOTA
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification arXiv:2101.07429
AutoMLonLIDC-IDRI
F1 score· 2021-01-19
0.8929
SOTA
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification arXiv:2101.07429
AutoMLonLIDC-IDRI
Specificity (VEB+)· 2021-01-19
95.04
SOTA
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification arXiv:2101.07429

Medical1 result

Lung Nodule ClassificationonLIDC-IDRI
Accuracy· 2021-01-19
90.77
best: 94.11 (ProCAN)
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules Classification arXiv:2101.07429