Evidence map›Paper›PMID 34693407›Full record

ArticleProceedings of the Future Technologies Conference (FTC) 2020. Future Technologies Conference (2020 : Online)2021

Deep Learning Methods for Anatomical Landmark Detection in Video Capsule Endoscopy Images.

Sodiq Adewole, Michelle Yeghyayan, Dylan Hyatt, Lubaina Ehsan, James Jablonski, Andrew Copland, Sana Syed, Donald Brown

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the Future Technologies Conference (FTC) 2020. Future Technologies Conference (2020 : Online), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

8 authors.

Sodiq AdewoleDepartment of Systems and Information Engineering, University of Virginia, Charlottesville, VA, USA.
Michelle YeghyayanDepartment of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, USA.
Dylan HyattDepartment of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, USA.
Lubaina EhsanDepartment of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, USA.
James JablonskiDepartment of Systems and Information Engineering, University of Virginia, Charlottesville, VA, USA.
Andrew CoplandDepartment of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, USA.
Sana SyedDepartment of Pediatrics, School of Medicine, University of Virginia, Charlottesville, VA, USA.
Donald BrownDepartment of Systems and Information Engineering, University of Virginia, Charlottesville, VA, USA.

Funding

Computational Characterization of Environmental EnteropathyK23DK117061 · NIDDK · UNIVERSITY OF VIRGINIA · PI SYED, SANA · 2019 to 2023
$964k
NIDDK NIH HHS K23 DK117061
6 · The paper itself

Abstract

Video capsule endoscope (VCE) is an emerging technology that allows examination of the entire gastrointestinal (GI) tract with minimal invasion. While traditional

Indexed as

AlexNetConvolutional neural networkGastrointestinal tractGoogLeNetGradient-weighted class activation mapping (Grad-CAM)ResNetVGG-netVideo capsule endoscopy

Identifiers

PMID34693407
PMCPMC8528446

What OpenQuestion holds

Textmetadata
LicenceTDM
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.