SOTAVerified

Lung Nodule Classification

Papers

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Showing 1–25 of 35 papers

TitleStatusHype
Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2Code1
Variational Autoencoders for Feature Exploration and Malignancy Prediction of Lung LesionsCode1
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules ClassificationCode1
Lung nodule detection and classification from Thorax CT-scan using RetinaNet with transfer learningCode1
Self-DenseMobileNet: A Robust Framework for Lung Nodule Classification using Self-ONN and Stacking-based Meta-Classifier—0
Lung cancer detection from thoracic CT scans using an ensemble of deep learning modelsCode0
Are Deep Learning Classification Results Obtained on CT Scans Fair and Interpretable?—0
Wavelet leader based formalism to compute multifractal features for classifying lung nodules in X-ray images—0
Deep fusion of gray level co-occurrence matrices for lung nodule classification—0
Faithful learning with sure data for lung nodule diagnosis—0
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification—0
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data—0
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics—0
Meta ordinal weighting net for improving lung nodule classification—0
3D Axial-Attention for Lung Nodule Classification—0
Meta Ordinal Regression Forest For Learning with Unsure Lung Nodules—0
ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification—0
Lung Nodule Classification Using Biomarkers, Volumetric Radiomics and 3D CNNs—0
Contraction Mapping of Feature Norms for Classifier Learning on the Data with Different Quality—0
Radiomic feature selection for lung cancer classifiers—0
Lung Nodule Classification using Deep Local-Global NetworksCode0
Multi-level CNN for lung nodule classification with Gaussian Process assisted hyperparameter optimizationCode0
Gated-Dilated Networks for Lung Nodule Classification in CT scans—0
Shape and Margin-Aware Lung Nodule Classification in Low-dose CT Images via Soft Activation Mapping—0
Classification of lung nodules in CT images based on Wasserstein distance in differential geometry—0
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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