Evidence map›Paper›PMID 39929844›Full record

ArticleScientific data2025

Renji endoscopic submucosal dissection video data set for early gastric cancer.

Jinnan Chen, Xiangning Zhang, Chunjiang Gu, Tang Cao, Jinneng Wang, Zhao Li, Yiming Song, Liuyi Yang, Zhengjie Zhang, Qingwei Zhang and 2 more

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. A novel wearable interface based on IMUs for robotic endoscopy.International journal of computer assisted radiology and surgery · 2026
    Article
  2. 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

12 authors.

Jinnan Chen *Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Xiangning Zhang *School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Chunjiang Gu *Department of Gastroenterology, Liangping District Peoples Hospital of Chongqing, Chongqing, China.
Tang CaoDepartment of Gastroenterology, The First Branch, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jinneng WangDepartment of Gastroenterology, Beibei Hospital of Chongqing Medical University (The Ninth People's Hospital of Chongqing), Chongqing, China.
Zhao LiDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Yiming SongDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Liuyi YangDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Zhengjie ZhangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Qingwei ZhangDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China. zhangqingweif@hotmail.com.
Dahong QianSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. dahong.qian@sjtu.edu.cn.
Xiaobo LiDivision of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China. lxb_1969@163.com.

Funding

Science and Technology Commission of Shanghai Municipality (Shanghai Municipal Science and Technology Commission) 23Y11905300
6 · The paper itself

Abstract

In recent years, the progress of artificial intelligence has greatly advanced computer-assisted intervention, surgical learning, and postoperative surgical video analysis techniques, greatly improving the skill levels of surgeons and overall outcomes. Deep learning based endoscopic surgery phase recognition has a very high dependency on large-scale datasets and annotations. This study introduces the Renji endoscopic submucosal dissection (ESD) video dataset for early gastric cancer (EGC), comprising 20 ESD endoscopic videos and 66,656 phase recognition annotations jointly annotated by three endoscopists. To the best of our knowledge, this is the first publicly available ESD dataset for the treatment of EGC, and we believe this work will contribute to the standardization of ESD dataset construction. The dataset and annotations are publicly available in Figshare.

Indexed as

Endoscopic Mucosal ResectionStomach NeoplasmsDeep LearningHumansVideo Recording

Identifiers

PMID39929844
PMCPMC11811142

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.