SOTAVerified

Cancer Classification

Papers

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Showing 76–100 of 208 papers

TitleStatusHype
Exploring Patient Data Requirements in Training Effective AI Models for MRI-based Breast Cancer Classification—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
Adversarial Attacks and Defences for Skin Cancer Classification—0
Adaptive Deep Learning for Multiclass Breast Cancer Classification via Misprediction Risk Analysis—0
A CNN toolbox for skin cancer classification—0
Breast Cancer Classification Using: Pixel Interpolation—0
Breast Cancer Classification Using Gradient Boosting Algorithms Focusing on Reducing the False Negative and SHAP for Explainability—0
A new parsimonious method for classifying Cancer Tissue-of-Origin Based on DNA Methylation 450K data—0
Dual-Activated Lightweight Attention ResNet50 for Automatic Histopathology Breast Cancer Image Classification—0
Breast Cancer Classification using Deep Learned Features Boosted with Handcrafted Features—0
Efficient Lung Cancer Image Classification and Segmentation Algorithm Based on Improved Swin Transformer—0
Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework—0
An evaluation of DNA-damage response and cell-cycle pathways for breast cancer classification—0
Enhancing Non-mass Breast Ultrasound Cancer Classification With Knowledge Transfer—0
Advances in Multiple Instance Learning for Whole Slide Image Analysis: Techniques, Challenges, and Future Directions—0
Evaluation of Multi-Scale Multiple Instance Learning to Improve Thyroid Cancer Classification—0
Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography—0
Double Integral Enhanced Zeroing Neural Network Optimized with ALSOA fostered Lung Cancer Classification using CT Images—0
Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation—0
Exploring Machine Learning Models for Lung Cancer Level Classification: A comparative ML Approach—0
Breast Cancer classification by adaptive weighted average ensemble of previously trained models—0
Feasibility of Colon Cancer Detection in Confocal Laser Microscopy Images Using Convolution Neural Networks—0
An Efficient Binary Harris Hawks Optimization based on Quantum SVM for Cancer Classification Tasks—0
Domain Adaptation for Deviating Acquisition Protocols in CNN-based Lesion Classification on Diffusion-Weighted MR Images—0
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Benchmark Results

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