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Updated: Jul 17, 2025

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Medical visual question answering: A survey.

Zhihong Lin1, Donghao Zhang2, Qingyi Tao3

  • 1Faculty of Engineering, Monash University, Clayton, VIC, 3800, Australia.

Artificial Intelligence in Medicine
|September 6, 2023
PubMed
Summary
This summary is machine-generated.

This survey explores medical visual question answering (VQA) systems, which use artificial intelligence to answer clinical questions about medical images. It reviews datasets, methods, and challenges to guide future research in this specialized AI field.

Keywords:
Computer visionMedical image interpretationNatural language processingVisual question answering

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Area of Science:

  • Artificial Intelligence
  • Medical Imaging Analysis
  • Computer Vision

Background:

  • Medical Visual Question Answering (VQA) integrates artificial intelligence with visual question answering challenges.
  • Existing general-domain VQA research requires specific exploration for medical applications due to unique task characteristics.

Purpose of the Study:

  • To provide a comprehensive overview of the current state of medical VQA.
  • To identify and discuss publicly available medical VQA datasets, including their sources, size, and features.
  • To review and analyze existing approaches, their innovations, and potential advancements in medical VQA.

Main Methods:

  • Systematic collection and discussion of up-to-date, publicly available medical VQA datasets.
  • Review and summarization of techniques and innovations employed in medical VQA tasks.
  • Analysis of medical-specific challenges and future research directions.

Main Results:

  • Catalog of current medical VQA datasets with details on data characteristics.
  • Summary of diverse methodologies applied to medical VQA.
  • Identification of key challenges and promising avenues for future research in the field.

Conclusions:

  • The field of medical VQA requires dedicated investigation due to its specialized nature.
  • This survey offers valuable insights for researchers entering the medical VQA domain.
  • Further research is encouraged to address identified challenges and advance medical AI capabilities.