Evidence map›Paper›PMID 40454291›Full record

ReviewHSS journal : the musculoskeletal journal of Hospital for Special Surgery2025

Large Language Models in Spine Surgery: A Promising Technology.

Romil Shah, Joseph H Schwab

Abstract readReview
In one paragraph

Review in HSS journal : the musculoskeletal journal of Hospital for Special Surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Large language models for lumbar spondylolisthesis detection: a multi-center pilot comparative radiographic accuracy study.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2026
    Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Romil ShahCedars Sinai Department of Orthopedic Surgery, Los Angeles, CA, USA.ORCID https://orcid.org/0000-0001-7459-4831
Joseph H SchwabCedars Sinai Department of Orthopedic Surgery, Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

artificial intelligencelarge language modelsmachine learningnatural language processingorthopedic surgeryspine surgerytechnology integration

Identifiers

PMID40454291
PMCPMC12125007

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.