mlsanityData to 7 Oct 2026

Multiple Meta-model Quantifying for Medical Visual Question Answering

arXiv 2105.08913 ↗First posted 19 May 2021cs.CVcited by 54

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Abstract (arXiv)

Transfer learning is an important step to extract meaningful features and overcome the data limitation in the medical Visual Question Answering (VQA) task. However, most of the existing medical VQA methods rely on external data for transfer learning, while the meta-data within the dataset is not fully utilized. In this paper, we present a new multiple meta-model quantifying method that effectively learns meta-annotation and leverages meaningful features to the medical VQA task. Our proposed method is designed to increase meta-data by auto-annotation, deal with noisy labels, and output meta-models which provide robust features for medical VQA tasks. Extensively experimental results on two public medical VQA datasets show that our approach achieves superior accuracy in comparison with other state-of-the-art methods, while does not require external data to train meta-models.

Key facts. Cited by 54 papers in the map (data through 7 Oct 2026). Builds on 25 of its 48 references that are in the map. First posted on arXiv 19 May 2021.

Builds on

25 of 48 references.

References · 25

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  4. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  5. 2017Prototypical Networks for Few-shot Learningcited by 3,001
  6. 2016Matching Networks for One Shot Learningcited by 2,246
  7. 2017Learning to Compare: Relation Network for Few-Shot Learningcited by 1,139
  8. 2018On First-Order Meta-Learning Algorithmscited by 1,003
  9. 2020PathVQA: 30000+ Questions for Medical Visual Question Answeringcited by 467
  10. 2018Bilinear Attention Networkscited by 277
  11. 2015Stacked Attention Networks for Image Question Answeringcited by 273
  12. 2017Meta Networkscited by 268
13 more
  1. 2016Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Groundingcited by 243
  2. 2018Unsupervised Learning via Meta-Learningcited by 81
  3. 2018Unsupervised Meta-Learning For Few-Shot Image Classificationcited by 74
  4. 2019Overcoming Data Limitation in Medical Visual Question Answeringcited by 71
  5. 2019Compact Trilinear Interaction for Visual Question Answeringcited by 24
  6. 2020A Question-Centric Model for Visual Question Answering in Medical Imagingcited by 23
  7. 2020End-to-End Real-time Catheter Segmentation with Optical Flow-Guided Warping during Endovascular Interventioncited by 20
  8. 2020Pathological Visual Question Answeringcited by 18
  9. 2020Autonomous Navigation in Complex Environments with Deep Multimodal Fusion Networkcited by 16
  10. 2018Training Medical Image Analysis Systems like Radiologistscited by 13
  11. 2020Hierarchical Deep Multi-modal Network for Medical Visual Question Answeringcited by 11
  12. 2019Leveraging Medical Visual Question Answering with Supporting Factscited by 4
  13. 2019Scene Understanding for Autonomous Manipulation with Deep Learningcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 7; 2023: 17; 2024: 14; 2025: 8; 2026: 1.

54 papers.

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  1. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 162
  2. 2021Medical Visual Question Answering: A Surveycited by 93
  3. 2023Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Modelscited by 58
  4. 2023PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathologycited by 57
  5. 2023A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysiscited by 37
  6. 2023RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-trainingcited by 31
  7. 2023Q2ATransformer: Improving Medical VQA via an Answer Querying Decodercited by 31
  8. 2022Self-supervised vision-language pretraining for Medical visual question answeringcited by 30
  9. 2023A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosiscited by 30
  10. 2023Masked Vision and Language Pre-training with Unimodal and Multimodal Contrastive Losses for Medical Visual Question Answeringcited by 29
  11. 2023Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Modelscited by 28
  12. 2021Coarse-to-Fine Reasoning for Visual Question Answeringcited by 25
38 more
  1. 20253D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Taskscited by 24
  2. 2023Multi-task Paired Masking with Alignment Modeling for Medical Vision-Language Pre-trainingcited by 22
  3. 2021Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Imagescited by 21
  4. 2024PeFoMed: Parameter Efficient Fine-tuning of Multimodal Large Language Models for Medical Imagingcited by 21
  5. 2024Biomedical Visual Instruction Tuning with Clinician Preference Alignmentcited by 21
  6. 2024MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integrationcited by 21
  7. 2021Global-Local Attention for Emotion Recognitioncited by 20
  8. 2024Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Surveycited by 20
  9. 2023Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reportingcited by 17
  10. 2024Surgical-VQLA++: Adversarial Contrastive Learning for Calibrated Robust Visual Question-Localized Answering in Robotic Surgerycited by 17
  11. 2023Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learningcited by 16
  12. 2022RepsNet: Combining Vision with Language for Automated Medical Reportscited by 14
  13. 2024MISS: A Generative Pretraining and Finetuning Approach for Med-VQAcited by 14
  14. 2024MedThink: Explaining Medical Visual Question Answering via Multimodal Decision-Making Rationalecited by 14
  15. 2021A Survey of Natural Language Generationcited by 13
  16. 2023A scoping review on multimodal deep learning in biomedical images and textscited by 13
  17. 2021Light-weight Deformable Registration using Adversarial Learning with Distilling Knowledgecited by 12
  18. 2024LaPA: Latent Prompt Assist Model For Medical Visual Question Answeringcited by 12
  19. 2024Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Modelscited by 11
  20. 2024A Survey of Medical Vision-and-Language Applications and Their Techniquescited by 11
  21. 2024Pretraining Vision-Language Model for Difference Visual Question Answering in Longitudinal Chest X-rayscited by 9
  22. 2022Fine-Grained Visual Classification using Self Assessment Classifiercited by 8
  23. 2024A Systematic Review of Generalization Research in Medical Image Classificationcited by 8
  24. 2022UnICLAM:Contrastive Representation Learning with Adversarial Masking for Unified and Interpretable Medical Vision Question Answeringcited by 6
  25. 2023Logical Implications for Visual Question Answering Consistencycited by 6
  26. 2022A Dual-Attention Learning Network with Word and Sentence Embedding for Medical Visual Question Answeringcited by 5
  27. 2023Localized Questions in Medical Visual Question Answeringcited by 5
  28. 2023MedXChat: A Unified Multimodal Large Language Model Framework towards CXRs Understanding and Generationcited by 5
  29. 2021MuVAM: A Multi-View Attention-based Model for Medical Visual Question Answeringcited by 4
  30. 2023BESTMVQA: A Benchmark Evaluation System for Medical Visual Question Answeringcited by 3
  31. 2025Grounding Chest X-Ray Visual Question Answering with Generated Radiology Reportscited by 3
  32. 2025DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labelscited by 2
  33. 2024Benchmarking Vision-Language Contrastive Methods for Medical Representation Learningcited by 1
  34. 2025Cause-Effect Driven Optimization for Robust Medical Visual Question Answering with Language Biasescited by 1
  35. 2025Barriers in Integrating Medical Visual Question Answering into Radiology Workflows: A Scoping Review and Clinicians' Insightscited by 1
  36. 2025Alignment, Mining and Fusion: Representation Alignment with Hard Negative Mining and Selective Knowledge Fusion for Medical Visual Question Answeringcited by 1
  37. 2022Barlow constrained optimization for Visual Question Answeringcited by 0
  38. 2022Scoliosis Detection using Deep Neural Networkcited by 0

50 most cited of 54 All 54 (JSON)