<scp>MicroRAG</scp> : Development of a Novel Artificial Intelligence Retrieval‐Augmented Generation Model for Microsurgery Clinical Decision Support
MicroRAG represents a technological innovation in microsurgical practice, providing instant access to evidence-based recommendations that typically require hours of literature review. By delivering comprehensive, literature-grounded guidance in real-time, this system has the potential to standardize best practices, reduce decision-making uncertainty, and ultimately improve patient outcomes across all levels of surgical experience.
Authors
- Dinesh Kumar Singh (ORCID: https://orcid.org/0000-0002-3594-2431)
- Kavach Shah
- Eugene Pinsky (ORCID: https://orcid.org/0000-0002-3836-1851)
- Steven Schulz (ORCID: https://orcid.org/0009-0001-2384-894X)
- Berk B. Özmen (ORCID: https://orcid.org/0000-0001-7803-1868)
- Nishant Singh (ORCID: https://orcid.org/0000-0003-3368-1511)
- İbrahim Berber (ORCID: https://orcid.org/0000-0002-6618-8347)
- Sarah N. Bishop (ORCID: https://orcid.org/0000-0002-7660-7576)
- Steven Bernard (ORCID: https://orcid.org/0000-0003-1663-9469)
- Risal Djohan
- Graham S. Schwarz (ORCID: https://orcid.org/0009-0009-8553-6819)
Institutions
- Boston University (US)
- Cleveland Clinic (US)
- University of Massachusetts Boston (US)
- Case Western Reserve University (US)
Publication Details
- Journal
- Microsurgery
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1002/micr.70138
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31