Evidence map›Paper›PMID 42891058›Full record

ReviewFrontiers in artificial intelligence2026

Beyond diagnostic accuracy: navigating the artificial intelligence data tsunami toward value-based implementation in gastroenterology.

Konstantinos Ekmektzoglou, Theodore Rokkas

Abstract readReview
In one paragraph

Review in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Konstantinos EkmektzoglouMedical School, European University of Cyprus, Nicosia, Cyprus.
Theodore RokkasMedical School, European University of Cyprus, Nicosia, Cyprus.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) in gastrointestinal (GI) endoscopy has evolved from its early application in simple edge detection to highly sophisticated technologies designed to improve detection of neoplastic and preneoplastic lesions and support clinical decision-making. However, this rapid technological evolution has generated a "

Indexed as

artificial intelligencecost-effectivenessdata tsunamigastroenterologyhuman factors

Identifiers

PMID42891058
PMCPMC13673138

What OpenQuestion holds

Textmetadata
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.