{"total":16,"rows":[{"id":"2403.13111","title":"Deep learning with noisy labels in medical prediction problems: a scoping review","created":"2024-03-19","cited_by_count":10,"area":null},{"id":"2308.04551","title":"Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining","created":"2023-08-08","cited_by_count":8,"area":null},{"id":"2403.12167","title":"A Systematic Review of Generalization Research in Medical Image Classification","created":"2024-03-18","cited_by_count":8,"area":null},{"id":"2207.00807","title":"Less is More: Adaptive Curriculum Learning for Thyroid Nodule Diagnosis","created":"2022-07-02","cited_by_count":6,"area":null},{"id":"2306.09718","title":"Label-noise-tolerant medical image classification via self-attention and self-supervised learning","created":"2023-06-16","cited_by_count":4,"area":null},{"id":"2407.05973","title":"Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise","created":"2024-07-08","cited_by_count":3,"area":null},{"id":"2401.07990","title":"How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?","created":"2024-01-15","cited_by_count":1,"area":null},{"id":"2406.12293","title":"Unleashing the Potential of Open-set Noisy Samples Against Label Noise for Medical Image Classification","created":"2024-06-18","cited_by_count":1,"area":null},{"id":"2510.12687","title":"EReLiFM: Evidential Reliability-Aware Residual Flow Meta-Learning for Open-Set Domain Generalization under Noisy Labels","created":"2025-10-14","cited_by_count":1,"area":null},{"id":"2203.15317","title":"Agreement or Disagreement in Noise-tolerant Mutual Learning?","created":"2022-03-29","cited_by_count":0,"area":null},{"id":"2207.04423","title":"Dual-Correction Adaptation Network for Noisy Knowledge Transfer","created":"2022-07-10","cited_by_count":0,"area":null},{"id":"2308.12737","title":"Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification","created":"2023-08-24","cited_by_count":0,"area":null},{"id":"2312.15233","title":"Sample selection with noise rate estimation in noise learning of medical image analysis","created":"2023-12-23","cited_by_count":0,"area":null},{"id":"2404.04800","title":"Coordinated Sparse Recovery of Label Noise","created":"2024-04-07","cited_by_count":0,"area":null},{"id":"2505.18741","title":"MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images","created":"2025-05-24","cited_by_count":0,"area":null},{"id":"2510.08393","title":"Robust Source-Free Domain Adaptation for Medical Image Segmentation based on Curriculum Learning","created":"2025-10-09","cited_by_count":0,"area":null}],"next_cursor":null}