Evidence map›Paper›PMID 32456309›Full record

ArticleJournal of clinical medicine2020

Automated Classification of Colorectal Neoplasms in White-Light Colonoscopy Images via Deep Learning.

Young Joo Yang, Bum-Joo Cho, Myung-Je Lee, Ju Han Kim, Hyun Lim, Chang Seok Bang, Hae Min Jeong, Ji Taek Hong, Gwang Ho Baik

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. A Systematic Review and Meta-analysis of Convolutional Neural Network in the Diagnosis of Colorectal Polyps and Cancer.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2023
    Pooled it
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  6. Review
  7. Role of Artificial Intelligence in Endoscopic Intervention: A Clinical Review.Journal of community hospital internal medicine perspectives · 2024
    Review
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  16. Artificial Intelligence in Endoscopy.Digestive diseases and sciences · 2022
    Review
  17. Review
  18. Artificial intelligence in colonoscopy.World journal of gastroenterology · 2021
    Review
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  20. 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.

Young Joo YangDepartment of Internal Medicine, Hallym University College of Medicine, Chuncheon 24252, Korea.
Bum-Joo ChoMedical Artificial Intelligence Center, Hallym University Medical Center, Anyang 14068, Korea.ORCID 0000-0002-0244-388X
Myung-Je LeeMedical Artificial Intelligence Center, Hallym University Medical Center, Anyang 14068, Korea.ORCID 0000-0002-2877-0619
Ju Han KimDivision of Biomedical Informatics, Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 03080, Korea.
Hyun LimDepartment of Internal Medicine, Hallym University College of Medicine, Chuncheon 24252, Korea.ORCID 0000-0001-6581-6420
Chang Seok BangDepartment of Internal Medicine, Hallym University College of Medicine, Chuncheon 24252, Korea.
Hae Min JeongDepartment of Internal Medicine, Hallym University College of Medicine, Chuncheon 24252, Korea.
Ji Taek HongDepartment of Internal Medicine, Hallym University College of Medicine, Chuncheon 24252, Korea.
Gwang Ho BaikDepartment of Internal Medicine, Hallym University College of Medicine, Chuncheon 24252, Korea.

Funding

Hallym University Research Fund HURF-2018-22Ministry of Science and ICT, South Korea NRF-2017M3A9E8033207
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial intelligencecolonoscopycolorectal neoplasmconvolutional neural networkdeep learning

Identifiers

PMID32456309
PMCPMC7291169

What OpenQuestion holds

Textmetadata
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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.