Evidence map›Paper›PMID 34671724›Full record

ReviewTherapeutic advances in gastrointestinal endoscopy

'Artificial intelligence in Barrett's Esophagus'.

Nour Hamade, Prateek Sharma

Open access · goldAbstract readReview
In one paragraph

Review in Therapeutic advances in gastrointestinal endoscopy. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Advances in the Diagnosis of Barrett's Esophagus.Diagnostics (Basel, Switzerland) · 2026
    Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Barrett's Esophagus: An Updated Review.Diagnostics (Basel, Switzerland) · 2023
    Review
  8. 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 at 2 institutions in 1 country.

Nour HamadeDepartment of Gastroenterology and Hepatology, School of Medicine, Indiana University, Indianapolis, IN, USA.ORCID https://orcid.org/0000-0003-0214-158X
Prateek SharmaDivision of Gastroenterology and Hepatology, Veteran Affairs Medical Center, 4801 E. Linwood Boulevard, Kansas City, MO 6412, USA.
Indiana University – Purdue University Indianapolis · USUniversity of Kansas · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite advances in endoscopic imaging modalities, there are still significant miss rates of dysplasia and cancer in Barrett's esophagus. Artificial intelligence (AI) is a promising tool that may potentially be a useful adjunct to the endoscopist in detecting subtle dysplasia and cancer. Studies have shown AI systems have a sensitivity of more than 90% and specificity of more than 80% in detecting Barrett's related dysplasia and cancer. Beyond visual detection and diagnosis, AI may also prove to be useful in quality control, streamlining clinical work, documentation, and lessening the administrative load on physicians. Research in this area is advancing at a rapid rate, and as the field expands, regulations and guidelines will need to be put into place to better regulate the growth and use of AI. This review provides an overview of the present and future role of AI in Barrett's esophagus.

Indexed as

endoscopyesophagusimagingpre-canceroustechnology

Identifiers

PMID34671724
PMCPMC8521738
OpenAlexW3206471777

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.