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Updated: Apr 14, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Large Language Models in Surgery: Promise, Pitfalls, and Practical Use.

Danette T Denham1, Colin Y Wang1, Emil Maric1

  • 1Division of Gastrointestinal and General Surgery, Department of Surgery, Endeavor Health, Evanston, IL, United States.

Journal of Abdominal Wall Surgery : JAWS
|April 13, 2026
PubMed
Summary

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Large Language Models (LLMs) offer surgeons practical AI tools for clinical workflows and patient communication. Careful implementation, including prompt engineering and privacy protection, is crucial for safe and effective use in surgical practice.

Area of Science:

  • Artificial Intelligence in Medicine
  • Surgical Technology
  • Clinical Informatics

Background:

  • AI-related medical publications surged 36-fold (2000-2022), yet practical surgical guidance lags.
  • Large Language Models (LLMs) are emerging AI tools with broad medical applications.
  • This review focuses on LLMs' pragmatic use in surgery, addressing limitations and ethics.

Purpose of the Study:

  • To delineate pragmatic applications of LLMs in surgical practice.
  • To address key limitations, implementation considerations, and ethical concerns of LLMs for surgeons.
  • To evaluate LLM benefits, constraints, and risk mitigation for surgical workflows and communication.

Main Methods:

  • Reviewed contemporary LLM platforms and their integration into clinical workflows.
Keywords:
academic researchartificial intelligence (AI)large language modelspatient outcomessurgery

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  • Assessed LLM utility in patient communication, surgical research, and academic writing.
  • Evaluated benefits, constraints, and risk mitigation strategies for surgeons.

    • Main Results:

    • LLMs enhance clinical workflows via ambient documentation and data summarization.
    • LLMs improve patient communication by simplifying information and tailoring messages.
    • LLMs aid surgical research through literature review and study design optimization.
    • Constraints include prompt engineering needs, hallucination risks, PHI protection, and ambiguous liability.

    Conclusions:

    • LLMs provide valuable tools for surgical efficiency and patient communication with proper oversight.
    • Successful LLM integration requires prompt engineering, fact-checking, privacy protection, and human judgment.
    • Surgeons must understand LLM limitations and ethical considerations for effective deployment.