SOTAVerified

Lung Nodule Classification

Papers

Showing 21–30 of 35 papers

TitleStatusHype
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics—0
Lung Cancer Screening Using Adaptive Memory-Augmented Recurrent Networks—0
Lung Nodule Classification by the Combination of Fusion Classifier and Cascaded Convolutional Neural Networks—0
Lung Nodule Classification Using Biomarkers, Volumetric Radiomics and 3D CNNs—0
Meta Ordinal Regression Forest For Learning with Unsure Lung Nodules—0
Meta ordinal weighting net for improving lung nodule classification—0
Multi-stage Neural Networks with Single-sided Classifiers for False Positive Reduction and its Evaluation using Lung X-ray CT Images—0
ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification—0
Radiomic feature selection for lung cancer classifiers—0
Lung cancer detection from thoracic CT scans using an ensemble of deep learning modelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MSTAUC95—Unverified
2ProCANAccuracy94.11—Unverified
3GVAEAccuracy93.1—Unverified
4Gated-DilatedAccuracy92.57—Unverified
5NASLung (ours)Accuracy90.77—Unverified
6DeepLungAccuracy90.44—Unverified
7Local-GlobalAccuracy88.46—Unverified
8I3DR-NetAUC81.84—Unverified