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Cited by 5Artificial Intelligence in Healthcare and EducationTechnology and Human Factors in Education and HealthArtificial Intelligence in Healthcare

Large Language Models in Spine Surgery: A Promising Technology

Open access
Shah, Romil, Schwab, Joseph H.·2025·HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery
DOI 10.1177/15563316251340696
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Abstract

Large language models (LLMs) offer potential applications across medical specialties; in spine surgery, opportunities exist to enhance patient care, streamline research, and improve clinical practice. This review explores the current and potential applications of LLMs in spine surgery, assessing their possibilities and limitations across patient education, research, clinical practice, and perioperative assistance.

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Registry

Crossref · 10.1177/15563316251340696

Cites

9 of 9 references verified0 citation errors · 0 not checkable

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  • Fabricated or hallucinated citations can create a false evidence base that is difficult for a busy clinician or a member of the lay public to verify.

    “Fabricated or hallucinated citations can create a false evidence base that is difficult for a busy clinician, much less a member of the lay public, to verify.8”

    From Large Language Model Hallucinations in Spine Surgery: A Comparative Analysis of Clinician vs Patient-Level Prompts (2026) · cites this paper as [8]

    The Clinical Practice section (page unavailable) reports that GPT-4 generated incorrect citations in half of its responses to neurosurgical questions, and the Discussion warns that hallucinations can produce misleading information. The paper does not say that these citations create a false evidence base or that busy clinicians or members of the public have difficulty verifying them. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • LLMs are being explored for utility in spine surgery research and patient education.

    “LLMs are being explored for their utility in spine surgery research and patient education, offering to simplify complex medical concepts for patients trying to understand their own conditions, improving healthcare literacy.7,8”

    From Large Language Model Hallucinations in Spine Surgery: A Comparative Analysis of Clinician vs Patient-Level Prompts (2026) · cites this paper as [8]

  • The utility of LLMs is limited by a significant and well-documented flaw: hallucinations.

    “The utility of these models is limited by a significant and well-documented flaw: hallucinations.8”

    From Large Language Model Hallucinations in Spine Surgery: A Comparative Analysis of Clinician vs Patient-Level Prompts (2026) · cites this paper as [8]

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Cites

Flagged first, then by citations

Research works printed but not linked: 31

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Cited by

Sorted by citations

Authors
Shah, R., & Schwab, J. H.
Affiliations
Cedars-Sinai Medical Center (US)
Corresponding author
Shah, Romil
ORCID
Venue
HSS Journal®: The Musculoskeletal Journal of Hospital for Special Surgery
Publisher
SAGE Publications
Published
2025-05-29
Volume
21
Issue
3
Pages
325-330
ISSN
  • 1556-3316 (ISSN-L)
  • 1556-3324
DOI
10.1177/15563316251340696
OpenAlex
W4410874125
Cited by
5
References
9
Citations by year
2026: 5
FWCI
0.26
Type
journal article
Language
en
Open access
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
  • HSS Journal® The Musculoskeletal Journal of Hospital for Special Surgery (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
Keywords
large language models, spinal surgery, patient education, clinical practice, medical research, artificial intelligence in healthcare

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