Evidence map›Paper›PMID 34447227›Full record

ReviewWorld journal of gastroenterology2021

Artificial intelligence in colonoscopy.

Joel Joseph, Ella Marie LePage, Catherine Phillips Cheney, Rishi Pawa

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in World journal of gastroenterology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. 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

4 authors.

Joel JosephDepartment of Internal Medicine, Wake Forest Baptist Medical Center, Winston Salem, NC 27157, United States.
Ella Marie LePageDepartment of Internal Medicine, Wake Forest Baptist Medical Center, Winston Salem, NC 27157, United States.
Catherine Phillips CheneyDepartment of Internal Medicine, Wake Forest School of Medicine, Winston Salem, NC 27157, United States.
Rishi PawaDepartment of Internal Medicine, Section of Gastroenterology and Hepatology, Wake Forest Baptist Medical Center, Winston-Salem, NC 27157, United States. rpawa@wakehealth.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer remains a leading cause of morbidity and mortality in the United States. Advances in artificial intelligence (AI), specifically computer aided detection and computer-aided diagnosis offer promising methods of increasing adenoma detection rates with the goal of removing more pre-cancerous polyps. Conversely, these methods also may allow for smaller non-cancerous lesions to be diagnosed

Indexed as

AdenomaColonic PolypsColorectal NeoplasmsArtificial IntelligenceColonoscopyHumansArtificial intelligenceCharacterizationColonoscopyComputer-aided detectionComputer-aided diagnosisDetection

Identifiers

PMID34447227
PMCPMC8371500

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.