Deep learning with noisy labels in medical prediction problems: a scoping review

Y Wei, Y Deng, C Sun, M Lin, H Jiang… - Journal of the American …, 2024 - academic.oup.com
Objectives Medical research faces substantial challenges from noisy labels attributed to
factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of …

Deep learning with noisy labels in medical prediction problems: a scoping review

Y Wei, Y Deng, C Sun, M Lin, H Jiang… - arXiv e-prints, 2024 - ui.adsabs.harvard.edu
Objectives: Medical research faces substantial challenges from noisy labels attributed to
factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of …

Deep learning with noisy labels in medical prediction problems: a scoping review

Y Wei, Y Deng, C Sun, M Lin, H Jiang… - Journal of the American …, 2024 - par.nsf.gov
ObjectivesMedical research faces substantial challenges from noisy labels attributed to
factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of …

Deep learning with noisy labels in medical prediction problems: a scoping review

Y Wei, Y Deng, C Sun, M Lin, H Jiang… - Journal of the American … - pubmed.ncbi.nlm.nih.gov
Objectives Medical research faces substantial challenges from noisy labels attributed to
factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of …

Deep learning with noisy labels in medical prediction problems: a scoping review.

Y Wei, Y Deng, C Sun, M Lin, H Jiang… - Journal of the American …, 2024 - europepmc.org
Objectives Medical research faces substantial challenges from noisy labels attributed to
factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of …

Deep learning with noisy labels in medical prediction problems: a scoping review

Y Wei, Y Deng, C Sun, M Lin, H Jiang… - arXiv preprint arXiv …, 2024 - arxiv.org
Objectives: Medical research faces substantial challenges from noisy labels attributed to
factors like inter-expert variability and machine-extracted labels. Despite this, the adoption of …