Medical visual question answering with multimodal: a systematic mini review (2023–2026) - Report - MDSpire

Medical visual question answering with multimodal: a systematic mini review (2023–2026)

  • By

  • Maimuna Biswas Noshin

  • Monoronjon Dutta

  • Md Nadim Kaysar

  • Rakib Hossain Sajib

  • Md Jakir Hossen

  • Dip Nandi

  • Abdullah Al Jubair

  • Mashiour Rahman

  • June 12, 2026

  • 0 min

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Clinical Report: A Systematic Mini Review of Multimodal Approaches in Medical Visual Question Answering

Overview

This systematic review analyzes recent advancements in Medical Visual Question Answering (Med-VQA), highlighting a shift towards multimodal frameworks that integrate visual and textual data.

Background

Medical Visual Question Answering (Med-VQA) is an evolving field that combines visual and textual information to assist in clinical decision-making. The integration of large language models (LLMs) and vision-language models (VLMs) has transformed traditional medical question answering methods.

Data Highlights

This review analyzed 27 studies published from 2023 to 2024, focusing on the evolution of Med-VQA systems.

Key Findings

  • Recent Med-VQA systems have transitioned from text-heavy approaches to multimodal frameworks.
  • Generative models, supported by retrieval mechanisms, provide more consistent responses than traditional methods.
  • Chain-of-Thought (CoT) and multi-agent frameworks enhance interpretability and reasoning in Med-VQA.
  • Limitations include increased computational time and challenges in real-world clinical settings.

Clinical Implications

Clinicians should be aware of the limitations and challenges associated with implementing these technologies in practice.

Conclusion

The systematic review highlights the progress in Med-VQA and the existing limitations.

Related Resources & Content

  1. Frontiers, Source, 2026 -- Medical Visual Question Answering with Multimodal: A Systematic Mini Review
  2. DIGITAL HEALTH — A linguistic lens into vision-language models for open-ended question-answers in medical visual question answering
  3. A Comprehensive Review of Multimodal Human-Computer Interaction Techniques in Interventional Radiology and Surgical Procedures
  4. npj Digital Medicine — Advancing Objective and Understandable Competency Evaluation: Improving Clinical Assessment with Multimodal AI and Anomaly Detection Techniques
  5. npj Digital Medicine — Integrated Machine Learning Approaches for Video-Based Assessment of Mental Health with a Single Question
  6. Marketing Submission Recommendations for a Predetermined Change Control Plan for Artificial Intelligence-Enabled Device Software Functions | FDA
  7. Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI)
  8. Frontiers | Medical Visual Question Answering with Multimodal: A Systematic Mini Review (2023-2026)

Original Source(s)

Medical visual question answering with multimodal: a systematic mini review (2023–2026)

  • by Maimuna Biswas Noshin, Monoronjon Dutta, Md Nadim Kaysar, Rakib Hossain Sajib, Md Jakir Hossen, Dip Nandi, Abdullah Al Jubair, Mashiour Rahman

  • June 12, 2026

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