Evidence map›Paper›PMID 37046611›Full record

ArticleCancers2023

Optical Biopsy of Dysplasia in Barrett's Oesophagus Assisted by Artificial Intelligence.

Jouke J H van der Laan, Joost A van der Putten, Xiaojuan Zhao, Arend Karrenbeld, Frans T M Peters, Jessie Westerhof, Peter H N de With, Fons van der Sommen, Wouter B Nagengast

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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

9 authors at 2 institutions in 1 country.

Jouke J H van der LaanDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.ORCID 0000-0001-6727-715X
Joost A van der PuttenDepartment of Electrical Engineering, Video Coding and Architectures, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.ORCID 0000-0002-0915-9048
Xiaojuan ZhaoDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.
Arend KarrenbeldDepartment of Pathology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.
Frans T M PetersDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.
Jessie WesterhofDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.
Peter H N de WithDepartment of Electrical Engineering, Video Coding and Architectures, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.
Fons van der SommenDepartment of Electrical Engineering, Video Coding and Architectures, Eindhoven University of Technology, 5612 AZ Eindhoven, The Netherlands.ORCID 0000-0002-3593-2356
Wouter B NagengastDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands.ORCID 0000-0002-6164-1536
University Medical Center Groningen · NLEindhoven University of Technology · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical biopsy in Barrett's oesophagus (BE) using endocytoscopy (EC) could optimize endoscopic screening. However, the identification of dysplasia is challenging due to the complex interpretation of the highly detailed images. Therefore, we assessed whether using artificial intelligence (AI) as second assessor could help gastroenterologists in interpreting endocytoscopic BE images. First, we prospectively videotaped 52 BE patients with EC. Then we trained and tested the AI pm distinct datasets drawn from 83,277 frames, developed an endocytoscopic BE classification system, and designed online training and testing modules. We invited two successive cohorts for these online modules: 10 endoscopists to validate the classification system and 12 gastroenterologists to evaluate AI as second assessor by providing six of them with the option to request AI assistance. Training the endoscopists in the classification system established an improved sensitivity of 90.0% (+32.67%,

Indexed as

Barrett’s dysplasiacomputer-aided diagnosisendocytoscopymachine learningmedical trainingsurveillance

Identifiers

PMID37046611
PMCPMC10093622
OpenAlexW4360856890

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.