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Related Experiment Video

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MicroRAG: Development of a Novel Artificial Intelligence Retrieval-Augmented Generation Model for Microsurgery

Berk B Ozmen1, Nishant Singh2, Kavach Shah2

  • 1Department of Plastic Surgery, Cleveland Clinic, Cleveland, Ohio, USA.

Microsurgery
|November 14, 2025
PubMed
Summary
This summary is machine-generated.

MicroRAG, the first AI clinical decision support system for microsurgery, offers instant, evidence-based recommendations by synthesizing surgical literature. This tool enhances decision-making and improves patient outcomes.

Keywords:
artificial intelligenceclinical decision supportlarge language modelsmicrosurgeryretrieval‐augmented generation

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Area of Science:

  • Microsurgery and Artificial Intelligence
  • Clinical Decision Support Systems
  • Medical Literature Synthesis

Background:

  • Microsurgical decisions integrate patient factors, techniques, and intraoperative data.
  • Existing AI, large language models (LLMs), and retrieval-augmented generation (RAG) lack microsurgery-specific clinical decision support.
  • MicroRAG is the first AI system for microsurgery, providing instant, evidence-based recommendations from the literature.

Purpose of the Study:

  • To develop and evaluate MicroRAG, an AI-powered clinical decision support system for microsurgery.
  • To leverage retrieval-augmented generation (RAG) technology for real-time, literature-backed guidance.
  • To address the need for integrated decision support in complex microsurgical scenarios.

Main Methods:

  • Developed an AI system integrating 4876 microsurgical publications (2000-2024) using RAG.
  • Implemented hierarchical document clustering for query processing.
  • Evaluated performance on 10 clinical scenarios measuring relevancy, faithfulness, and accuracy.

Main Results:

  • MicroRAG achieved high relevancy (0.953) and faithfulness (0.907) scores.
  • System demonstrated strong correctness (0.88) and semantic similarity (0.75).
  • Provided actionable guidance for free flap monitoring, complication management, and technique selection, all literature-grounded.

Conclusions:

  • MicroRAG offers a technological innovation for microsurgery, enabling instant access to evidence-based recommendations.
  • The system can standardize best practices and reduce decision-making uncertainty.
  • Potential to improve patient outcomes across all experience levels in microsurgery.