Cited by 101Artificial Intelligence in Healthcare and EducationMachine Learning in HealthcareArtificial Intelligence in Education

On the cusp: considering the impact of artificial intelligence language models in healthcare

Open access
Goodman, Rachel S., Patrinely, J. Randall, Osterman, Travis, Wheless, Lee, Johnson, Douglas B.·2023·Med

Abstract

Goodman et al. discuss how AI technologies like the natural language processing model Chat-GPT could potentially transform healthcare through knowledge dissemination and personalized patient education. Before these tools can be safely integrated into healthcare, research and development of robust oversight mechanisms are necessary to ensure their accuracy and reliability.

Integrity signals

Registry

Crossref · 10.1016/j.medj.2023.02.008

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Goodman, R. S., Patrinely, J. R., Osterman, T., Wheless, L., & Johnson, D. B.
Affiliations
  • Vanderbilt University (US)
  • Vanderbilt University Medical Center (US)
Corresponding author
Johnson, Douglas B.
Venue
Med
Publisher
Elsevier BV
Published
2023-03
Volume
4
Issue
3
Pages
139-140
ISSN
2666-6340 (ISSN-L)
OpenAlex
W4323835279
Cited by
100
References
2
Citations by year
2026: 9 · 2025: 31 · 2024: 33 · 2023: 27
FWCI
3.99
Type
journal article
Language
en
Open access
Locations
  • Med (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Cancer Institute (R01CA227481)
  • Bristol-Myers Squibb
  • Incyte
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
Keywords
artificial intelligence in healthcare, large language models, ChatGPT, natural language processing, personalized patient education, knowledge dissemination, human oversight of AI
MeSH terms
Artificial Intelligence, Delivery of Health Care, Health Facilities, Humans, Natural Language Processing, Reproducibility of Results

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review