SOTAVerified

Cancer Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 208 papers

TitleStatusHype
Application of Machine Learning in Melanoma Detection and the Identification of 'Ugly Duckling' and Suspicious Naevi: A Review—0
Comparison among dimensionality reduction techniques based on Random Projection for cancer classification—0
A Smartphone based Application for Skin Cancer Classification Using Deep Learning with Clinical Images and Lesion Information—0
A lightweight deep learning pipeline with DRDA-Net and MobileNet for breast cancer classification—0
Attention Model Enhanced Network for Classification of Breast Cancer Image—0
Comparison of Deep Learning and Machine Learning Models and Frameworks for Skin Lesion Classification—0
Context-Aware Learning using Transferable Features for Classification of Breast Cancer Histology Images—0
A new parsimonious method for classifying Cancer Tissue-of-Origin Based on DNA Methylation 450K data—0
An evaluation of DNA-damage response and cell-cycle pathways for breast cancer classification—0
Advances in Multiple Instance Learning for Whole Slide Image Analysis: Techniques, Challenges, and Future Directions—0
Advanced Deep Learning Methodologies for Skin Cancer Classification in Prodromal Stages—0
Breast Cancer Classification Based on Histopathological Images Using a Deep Learning Capsule Network—0
Biomarker Gene Identification for Breast Cancer Classification—0
An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification—0
Active Learning Enhances Classification of Histopathology Whole Slide Images with Attention-based Multiple Instance Learning—0
Breast Cancer classification by adaptive weighted average ensemble of previously trained models—0
An Efficient Binary Harris Hawks Optimization based on Quantum SVM for Cancer Classification Tasks—0
Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework—0
Breast Cancer Classification using Deep Learned Features Boosted with Handcrafted Features—0
Breast Cancer Classification Using Gradient Boosting Algorithms Focusing on Reducing the False Negative and SHAP for Explainability—0
Breast Cancer Classification Using: Pixel Interpolation—0
Breast Cancer Classification with Ultrasound Images Based on SLIC—0
A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method—0
A Pan-cancer Classification Model using Multi-view Feature Selection Method and Ensemble Classifier—0
Comparative Analysis of Deep Learning Architectures for Breast Cancer Diagnosis Using the BreaKHis Dataset—0
Show:102550
← PrevPage 2 of 9Next →

Benchmark Results

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