SOTAVerified

Cancer Classification

Papers

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Showing 126–150 of 208 papers

TitleStatusHype
Probabilistic Multi-Task Feature Selection—0
ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification—0
Quantifying Cancer Likeness: A Statistical Approach for Pathological Image Diagnosis—0
Rad4XCNN: a new agnostic method for post-hoc global explanation of CNN-derived features by means of radiomics—0
Reliable Breast Cancer Molecular Subtype Prediction based on uncertainty-aware Bayesian Deep Learning by Mammography—0
Revisiting Invariant Learning for Out-of-Domain Generalization on Multi-Site Mammogram Datasets—0
SelectiveKD: A semi-supervised framework for cancer detection in DBT through Knowledge Distillation and Pseudo-labeling—0
Siamese Neural Networks for Skin Cancer Classification and New Class Detection using Clinical and Dermoscopic Image Datasets—0
Skin Cancer Classification using Inception Network and Transfer Learning—0
Skin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet—0
Sparse High-Dimensional Isotonic Regression—0
Stacking-Enhanced Bagging Ensemble Learning for Breast Cancer Classification with CNN—0
Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms—0
Synthesizing lesions using contextual GANs improves breast cancer classification on mammograms—0
Theoretical Framework for Tempered Fractional Gradient Descent: Application to Breast Cancer Classification—0
Towards Out-of-Distribution Detection for breast cancer classification in Point-of-Care Ultrasound Imaging—0
Towards Robust Natural-Looking Mammography Lesion Synthesis on Ipsilateral Dual-Views Breast Cancer Analysis—0
Transfer learning with class-weighted and focal loss function for automatic skin cancer classification—0
Tree Ensembles with Rule Structured Horseshoe Regularization—0
Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation—0
Unsupervised Latent Stain Adaptation for Computational Pathology—0
USegMix: Unsupervised Segment Mix for Efficient Data Augmentation in Pathology Images—0
User lung cancer classification using efficientnet from ct scan images—0
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification—0
Validation of Conformal Prediction in Cervical Atypia Classification—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LASSO-MOGAT1:1 Accuracy95.9—Unverified
2LASSO-MOGAT1:1 Accuracy94.68—Unverified