Evidence map›Paper›PMID 40770268›Full record

ArticleScientific data2025

Renji endoscopic submucosal dissection video data set for colorectal neoplastic lesions.

Jinnan Chen, Xiangning Zhang, Jinneng Wang, Tang Cao, Chunjiang Gu, 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.
Jinneng Wang *Department of Gastroenterology, Beibei Hospital of Chongqing Medical University (The Ninth People's Hospital of Chongqing), Chongqing, China.
Tang CaoDepartment of Gastroenterology, The First Branch, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Chunjiang GuDepartment of Gastroenterology, Liangping District Peoples 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

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence advancements have significantly enhanced computer-aided intervention, learning among surgeons, and analysis of surgical videos post-operation, substantially elevating surgical expertise and patient outcomes. Recognition systems for endoscopic surgical phases using deep learning algorithms heavily rely on comprehensive annotated datasets. Our research presents the Renji dataset featuring videos of endoscopic submucosal dissection (ESD) for colorectal neoplastic lesions (CNLs), which includes 30 procedural recordings with 130,298 phase-specific annotations collaboratively labeled by a team of three specialists in endoscopy. To our knowledge, this represents the first openly accessible collection of ESD videos specifically targeting CNLs treatment, and we anticipate this work will help establish standards for constructing similar ESD databases. Both the video collection and corresponding annotations have been made publicly accessible through the Figshare platform.

Indexed as

Colorectal NeoplasmsEndoscopic Mucosal ResectionHumansVideo Recording

Identifiers

PMID40770268
PMCPMC12328798

What OpenQuestion holds

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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.