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TitleStatusHype
End-to-end Learning for Image-based Detection of Molecular Alterations in Digital Pathology—0
Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images AnalysisCode0
Multiple Instance Learning with Mixed Supervision in Gleason GradingCode1
Test-time image-to-image translation ensembling improves out-of-distribution generalization in histopathology—0
DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image ClassificationCode1
Incorporating intratumoral heterogeneity into weakly-supervised deep learning models via variance poolingCode1
DSCA: A Dual-Stream Network with Cross-Attention on Whole-Slide Image Pyramids for Cancer PrognosisCode1
Transformer-based Personalized Attention Mechanism for Medical Images with Clinical RecordsCode0
A comparative study between vision transformers and CNNs in digital pathology—0
A review of machine learning approaches, challenges and prospects for computational tumor pathology—0
Local Attention Graph-based Transformer for Multi-target Genetic Alteration PredictionCode1
A Deep Reinforcement Learning Framework for Rapid Diagnosis of Whole Slide Pathological Images—0
Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unlabeled, unannotated pathology slidesCode1
Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images—0
Contrastive learning-based computational histopathology predict differential expression of cancer driver genesCode0
Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology imagesCode2
Colorectal cancer survival prediction using deep distribution based multiple-instance learning—0
Evaluation of Multi-Scale Multiple Instance Learning to Improve Thyroid Cancer Classification—0
MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception LossCode1
From Modern CNNs to Vision Transformers: Assessing the Performance, Robustness, and Classification Strategies of Deep Learning Models in HistopathologyCode0
Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital HistopathologyCode2
Deep learning-based approach to reveal tumor mutational burden status from whole slide images across multiple cancer types—0
Hospital-Agnostic Image Representation Learning in Digital Pathology—0
Federated Learning for the Classification of Tumor Infiltrating Lymphocytes—0
Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutationCode1
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