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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Medical Artificial Intelligence for Early Detection of Lung Cancer: A Survey
Multi-Tiered Self-Contrastive Learning for Medical Microwave Radiometry (MWR) Breast Cancer Detection
MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule
Deep Learning-Based Channel Squeeze U-Structure for Lung Nodule Detection and Segmentation
Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detection
Task-Specific Data Preparation for Deep Learning to Reconstruct Structures of Interest from Severely Truncated CBCT Data
A study on Deep Convolutional Neural Networks, Transfer Learning and Ensemble Model for Breast Cancer Detection
Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study
BCDNet: A Fast Residual Neural Network For Invasive Ductal Carcinoma Detection
Improving Lung Cancer Diagnosis and Survival Prediction with Deep Learning and CT Imaging
Snuffy: Efficient Whole Slide Image Classifier
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data
OMG-Net: A Deep Learning Framework Deploying Segment Anything to Detect Pan-Cancer Mitotic Figures from Haematoxylin and Eosin-Stained Slides
Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review
D-MASTER: Mask Annealed Transformer for Unsupervised Domain Adaptation in Breast Cancer Detection from Mammograms
Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model
A Cross Spatio-Temporal Pathology-based Lung Nodule Dataset
Leveraging Knowledge Distillation for Lightweight Skin Cancer Classification: Balancing Accuracy and Computational Efficiency
A Wavelet Guided Attention Module for Skin Cancer Classification with Gradient-based Feature Fusion
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography
Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision
Mitigating annotation shift in cancer classification using single image generative models
Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography
No winners: Performance of lung cancer prediction models depends on screening-detected, incidental, and biopsied pulmonary nodule use cases
AI in Lung Health: Benchmarking Detection and Diagnostic Models Across Multiple CT Scan Datasets
Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method
Mammo-CLIP: Leveraging Contrastive Language-Image Pre-training (CLIP) for Enhanced Breast Cancer Diagnosis with Multi-view Mammography
Breast Cancer Image Classification Method Based on Deep Transfer Learning
Lung Cancer Detection Using Machine Learning Methods
Automated Report Generation for Lung Cytological Images Using a CNN Vision Classifier and Multiple-Transformer Text Decoders: Preliminary Study
Real-time respiratory motion forecasting with online learning of recurrent neural networks for accurate targeting in externally guided radiotherapy
NYCTALE: Neuro-Evidence Transformer for Adaptive and Personalized Lung Nodule Invasiveness Prediction
A Study of Acquisition Functions for Medical Imaging Deep Active Learning
BreastRegNet: A Deep Learning Framework for Registration of Breast Faxitron and Histopathology Images
Skin Cancer Segmentation and Classification Using Vision Transformer for Automatic Analysis in Dermatoscopy-based Non-invasive Digital System
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