Cancer Classification
1개 벤치마크 · 논문 260편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification
Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study
XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data
A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
Skin Lesion Synthesis with Generative Adversarial Networks
Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging
Papers
Semi-Supervised Learning-Based Genetic Biomarkers Dataset for Multiple-Stage Hepatocellular Carcinoma Prediction
Liver cancer is a complex disease responsible for a high number of deaths across the globe each year, making automated solutions for liver cancer classification urgent. The most common form of liver cancer is hepatocellu…
Cancer ClassificationToken-Based Dual-view Fusion and Adaptation of Large Vision Models for Breast Cancer Classification
Accurate breast cancer classification from mammography requires effective integration of complementary information from craniocaudal (CC) and mediolateral oblique (MLO) views, which provide a more complete characterizati…
Cancer ClassificationLearning Where to Look: A Reinforcement Learning Framework for Robust Micro-Ultrasound Prostate Cancer Detection
Micro-ultrasound ($μ$US) is a new, emerging, and promising imaging modality for prostate cancer (PCa) detection, but accurate identification of suspicious tissue remains highly dependent on clinical experience, leading t…
Reinforcement LearningCancer ClassificationMulti-cancer detection using a computationally efficient CNN with transfer learning
This study introduces a computationally efficient convolutional neural network (CNN) architecture enhanced with transfer learning for multi-cancer detection using biomedical images. The proposed lightweight CNN model is …
Cancer ClassificationTransfer LearningAn approach with Visual and Tabular Mamba to multimodal medical data using Mixed Fusion
This article presents a complementary approach for integrating multimodal medical data in cancer classification, based on state space models represented by the Mamba architecture. To this end, a mixed multimodal fusion a…
Cancer ClassificationTrusting Right Predictions for Wrong Reasons: A LIME Based Analysis of Deep Learning Interpretability in Lung Cancer Diagnosis
Lung cancer is the leading cause of cancer-related mortality, with approximately 2.5 million new cases and 1.8 million deaths annually, making reliable diagnosis a clinical priority. Although deep learning models have ac…
Cancer ClassificationLung Cancer Diagnosis