SOTAVerified

Cancer Classification

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 208 papers

TitleStatusHype
Advanced cervical cancer classification: enhancing pap smear images with hybrid PMD Filter-CLAHE—0
Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation—0
Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection—0
Investigating Quantum Feature Maps in Quantum Support Vector Machines for Lung Cancer Classification—0
Optimizing Deep Learning for Skin Cancer Classification: A Computationally Efficient CNN with Minimal Accuracy Trade-Off—0
An Artificial Intelligence Model for Early Stage Breast Cancer Detection from Biopsy Images—0
Validation of Conformal Prediction in Cervical Atypia Classification—0
Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework—0
Theoretical Framework for Tempered Fractional Gradient Descent: Application to Breast Cancer Classification—0
MSAD-Net: Multiscale and Spatial Attention-based Dense Network for Lung Cancer Classification—0
CytoFM: The first cytology foundation model—0
PathOrchestra: A Comprehensive Foundation Model for Computational Pathology with Over 100 Diverse Clinical-Grade Tasks—0
Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification, An Interpretable Multi-Omics Approach—0
Diffusion models applied to skin and oral cancer classification—0
Contrasting Low and High-Resolution Features for HER2 Scoring using Deep Learning—0
Adaptive Deep Learning for Multiclass Breast Cancer Classification via Misprediction Risk Analysis—0
Revisiting Invariant Learning for Out-of-Domain Generalization on Multi-Site Mammogram Datasets—0
Exploring Patient Data Requirements in Training Effective AI Models for MRI-based Breast Cancer Classification—0
Patch Stitching Data Augmentation for Cancer Classification in Pathology Images—0
USegMix: Unsupervised Segment Mix for Efficient Data Augmentation in Pathology Images—0
Triad: Vision Foundation Model for 3D Magnetic Resonance ImagingCode1
Joint Modelling Histology and Molecular Markers for Cancer ClassificationCode1
Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification—0
MEDFORM: A Foundation Model for Contrastive Learning of CT Imaging and Clinical Numeric Data in Multi-Cancer AnalysisCode0
Comparative Analysis of Hand-Crafted and Machine-Driven Histopathological Features for Prostate Cancer Classification and Segmentation—0
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Benchmark Results

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