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Continual Learning for Domain Adaptation in Chest X-ray Classification

arXiv 2001.05922 ↗First posted 16 Jan 2020cs.CV cs.LGcited by 31

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Abstract (arXiv)

Over the last years, Deep Learning has been successfully applied to a broad range of medical applications. Especially in the context of chest X-ray classification, results have been reported which are on par, or even superior to experienced radiologists. Despite this success in controlled experimental environments, it has been noted that the ability of Deep Learning models to generalize to data from a new domain (with potentially different tasks) is often limited. In order to address this challenge, we investigate techniques from the field of Continual Learning (CL) including Joint Training (JT), Elastic Weight Consolidation (EWC) and Learning Without Forgetting (LWF). Using the ChestX-ray14 and the MIMIC-CXR datasets, we demonstrate empirically that these methods provide promising options to improve the performance of Deep Learning models on a target domain and to mitigate effectively catastrophic forgetting for the source domain. To this end, the best overall performance was obtained using JT, while for LWF competitive results could be achieved - even without accessing data from the source domain.

Key facts. Cited by 31 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Jan 2020.

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Citing papers per year: 2021: 5; 2022: 8; 2023: 9; 2024: 8; 2025: 0; 2026: 1.

31 papers.

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  1. 2022Transformers in Medical Imaging: A Surveycited by 245
  2. 2021Online Coreset Selection for Rehearsal-based Continual Learningcited by 117
  3. 2021Deep Learning for Chest X-ray Analysis: A Surveycited by 84
  4. 2022LifeLonger: A Benchmark for Continual Disease Classificationcited by 28
  5. 2023ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysiscited by 25
  6. 2023Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectivescited by 24
  7. 2023Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospectscited by 22
  8. 2021Adversarial Continual Learning for Multi-Domain Hippocampal Segmentationcited by 14
  9. 2024BiasPruner: Debiased Continual Learning for Medical Image Classificationcited by 12
  10. 2023A Continual Learning Approach for Cross-Domain White Blood Cell Classificationcited by 10
  11. 2021Continual Active Learning for Efficient Adaptation of Machine Learning Models to Changing Image Acquisitioncited by 9
  12. 2024Continual Learning in Medical Imaging: A Survey and Practical Analysiscited by 9
19 more
  1. 2022Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Datacited by 8
  2. 2022Domain-Adaptive 3D Medical Image Synthesis: An Efficient Unsupervised Approachcited by 8
  3. 2023Generative appearance replay for continual unsupervised domain adaptationcited by 8
  4. 2022Continual Learning for Tumor Classification in Histopathology Imagescited by 6
  5. 2023Data efficient deep learning for medical image analysis: A surveycited by 6
  6. 2024Multi-Label Continual Learning for the Medical Domain: A Novel Benchmarkcited by 6
  7. 2022Re-examining Distillation For Continual Object Detectioncited by 5
  8. 2024Navigating Distribution Shifts in Medical Image Analysis: A Surveycited by 5
  9. 2022Federated Continual Learning to Detect Accounting Anomalies in Financial Auditingcited by 4
  10. 2023Few-shot Class-incremental Learning for Cross-domain Disease Classificationcited by 4
  11. 2021Continual Active Learning Using Pseudo-Domains for Limited Labelling Resources and Changing Acquisition Characteristicscited by 3
  12. 2023MLHOps: Machine Learning for Healthcare Operationscited by 2
  13. 2024Fairness Evolution in Continual Learning for Medical Imagingcited by 2
  14. 2024Is user feedback always informative? Retrieval Latent Defending for Semi-Supervised Domain Adaptation without Source Datacited by 2
  15. 2023Trustworthy Representation Learning Across Domainscited by 1
  16. 2024Continuous Unsupervised Domain Adaptation Using Stabilized Representations and Experience Replaycited by 1
  17. 2022External Attention Assisted Multi-Phase Splenic Vascular Injury Segmentation with Limited Datacited by 0
  18. 2024From Lab to Pocket: A Novel Continual Learning-based Mobile Application for Screening COVID-19cited by 0
  19. 2026CADRE: Stable, Parameter Efficient Adaptation of Medical Vision Language Models with Bounded Forgetting and Prior Driftcited by 0