Evidence map›Paper›PMID 39036586›Full record

ReviewJournal of community hospital internal medicine perspectives2024

Role of Artificial Intelligence in Endoscopic Intervention: A Clinical Review.

Nismat Javed, Haider Ghazanfar, Bhavna Balar, Harish Patel

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of community hospital internal medicine perspectives, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Nismat JavedDepartment of Internal Medicine, BronxCare Health System, Bronx, NY, USA.
Haider GhazanfarDepartment of Gastroenterology, BronxCare Health System, Bronx, NY, USA.
Bhavna BalarDepartment of Gastroenterology, BronxCare Health System, Bronx, NY, USA.
Harish PatelDepartment of Gastroenterology, BronxCare Health System, Bronx, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastrointestinal diseases are increasing in global prevalence. As a result, the contribution to both mortality and healthcare costs is increasing. While interventions utilizing scoping techniques or ultrasound are crucial to both the timely diagnosis and management of illness, a few limitations are associated with these techniques. Artificial intelligence, using computerized diagnoses, deep learning systems, or neural networks, is increasingly being employed in multiple aspects of medicine to improve the characteristics and outcomes of these tools. Therefore, this review aims to discuss applications of artificial intelligence in endoscopy, colonoscopy, and endoscopic ultrasound.

Indexed as

Artificial intelligenceCapsule endoscopyColonoscopyDetection rateEndoscopic ultrasoundEsophagogastroduodenoscopyGastrointestinal diseaseSensitivitySpecificity

Identifiers

PMID39036586
PMCPMC11259475

What OpenQuestion holds

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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.