mlsanityData to 14 Oct 2026

Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis

arXiv 2101.00318 ↗First posted 1 Jan 2021cs.CV cs.AI cs.LGcited by 18

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Abstract (arXiv)

Recent advances in unsupervised domain adaptation (UDA) show that transferable prototypical learning presents a powerful means for class conditional alignment, which encourages the closeness of cross-domain class centroids. However, the cross-domain inner-class compactness and the underlying fine-grained subtype structure remained largely underexplored. In this work, we propose to adaptively carry out the fine-grained subtype-aware alignment by explicitly enforcing the class-wise separation and subtype-wise compactness with intermediate pseudo labels. Our key insight is that the unlabeled subtypes of a class can be divergent to one another with different conditional and label shifts, while inheriting the local proximity within a subtype. The cases of with or without the prior information on subtype numbers are investigated to discover the underlying subtype structure in an online fashion. The proposed subtype-aware dynamic UDA achieves promising results on medical diagnosis tasks.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 28 of its 60 references that are in the map. First posted on arXiv 1 Jan 2021.

Builds on

28 of 60 references.

References · 28

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16 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 6; 2022: 7; 2023: 0; 2024: 4; 2025: 0; 2026: 1.

18 papers.

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  1. 2022Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectivescited by 98
  2. 2021Adapting Off-the-Shelf Source Segmenter for Target Medical Image Segmentationcited by 39
  3. 2021Generative Self-training for Cross-domain Unsupervised Tagged-to-Cine MRI Synthesiscited by 19
  4. 2021Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inferencecited by 18
  5. 2022Memory Consistent Unsupervised Off-the-Shelf Model Adaptation for Source-Relaxed Medical Image Segmentationcited by 15
  6. 2021Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptationcited by 10
  7. 2021Vision Transformer Hashing for Image Retrievalcited by 9
  8. 2022Self-semantic contour adaptation for cross modality brain tumor segmentationcited by 9
  9. 2022Unsupervised Domain Adaptation for Segmentation with Black-box Source Modelcited by 7
  10. 2024Navigating Distribution Shifts in Medical Image Analysis: A Surveycited by 5
  11. 2021Interpreting Depression From Question-wise Long-term Video Recording of SDS Evaluationcited by 4
  12. 2022Structure-aware Unsupervised Tagged-to-Cine MRI Synthesis with Self Disentanglementcited by 2
6 more
  1. 2022Subtype-Aware Dynamic Unsupervised Domain Adaptationcited by 2
  2. 2022Constraining Pseudo-label in Self-training Unsupervised Domain Adaptation with Energy-based Modelcited by 2
  3. 2024DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptationcited by 2
  4. 2024From Basic to Extra Features: Hypergraph Transformer Pretrain-then-Finetuning for Balanced Clinical Predictions on EHRcited by 1
  5. 2024Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion Recognitioncited by 0
  6. 2026When Normality Shifts: Risk-Aware Test-Time Adaptation for Unsupervised Tabular Anomaly Detectioncited by 0