Evidence map›Paper›PMID 39082468›Full record

ArticleAcademic emergency medicine : official journal of the Society for Academic Emergency Medicine2025

Enhancing emergency department charting: Using Generative Pre-trained Transformer-4 (GPT-4) to identify laceration repairs.

Jaskaran Karan Bains, Christopher Y K Williams, Drake Johnson, Hope Schwartz, Naina Sabbineni, Atul J Butte, Aaron E Kornblith

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Enhancing emergency department charting: Using Generative Pre-trained Transformer-4 (GPT-4) to identify laceration repairs.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2025
    Article
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

7 authors.

Jaskaran Karan BainsDepartment of Emergency Medicine, University of California, San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0001-7880-5878
Christopher Y K WilliamsBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
Drake JohnsonDepartment of Emergency Medicine, University of California, San Francisco, San Francisco, California, USA.
Hope SchwartzDepartment of Emergency Medicine, University of California, San Francisco, San Francisco, California, USA.
Naina SabbineniDepartment of Emergency Medicine, University of California, San Francisco, San Francisco, California, USA.
Atul J ButteBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
Aaron E KornblithDepartment of Emergency Medicine, University of California, San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0002-1344-575X

Funding

Accurate and Reliable Diagnostics for Injured Children: Machine Learning for UltrasoundK23HD110716 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Aaron Edward Kornblith · 2023 to 2026
$650k
Eunice Kennedy Shriver National Institute of Child Health and Human Development 1K23HD110716-01NICHD NIH HHS K23 HD110716
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Identifiers

PMID39082468
PMCPMC11726143

What OpenQuestion holds

Textmetadata
LicenceTDM
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.