Evidence map›Paper›PMID 38550997›Full record

ArticleiScience2024

Multi-step validation of a deep learning-based system with visual explanations for optical diagnosis of polyps with advanced features.

Qing-Wei Zhang, Zhengjie Zhang, Jianwei Xu, Zi-Hao Dai, Ran Zhao, Jian Huang, Hong Qiu, Zhao-Rong Tang, Bo Niu, Xun-Bing Zhang and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2024. 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. Review
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

18 authors.

Qing-Wei 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.
Zhengjie ZhangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Jianwei XuSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Zi-Hao DaiDivision 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.
Ran ZhaoDepartment of Gastroenterology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China.
Jian HuangDepartment of Gastroenterology, Yuyao People's Hospital, Medical School of Ningbo University, Ningbo, Zhejiang Province, China.
Hong QiuDepartment of Gastroenterology and Hepatology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
Zhao-Rong TangDepartment of Gastroenterology and Hepatology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
Bo NiuDepartment of Digestive Endoscopy Center, Yuncheng First Hospital, Yuncheng, Shanxi Province, China.
Xun-Bing ZhangDepartment of Digestive Endoscopy Center, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Peng-Fei WangFirst Division of Gastroenterology Department, Lanzhou University Second Hospital, Lanzhou, Gansu Province, China.
Mei YangDepartment of Gastroenterology and Hepatology, The Third People's Hospital of Chengdu, Chengdu, Sichuan Province, China.
Wan-Yin DengDepartment of Digestive Endoscopy Center, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, Fujian, China.
Yan-Sheng LinDepartment of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China.
Suncheng XiangSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Zhi-Zheng GeDivision 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.
Dahong QianSchool of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Xiao-Bo 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.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) has been found to assist in optical differentiation of hyperplastic and adenomatous colorectal polyps. We investigated whether AI can improve the accuracy of endoscopists' optical diagnosis of polyps with advanced features. We introduced our AI system distinguishing polyps with advanced features with more than 0.870 of accuracy in the internal and external validation datasets. All 19 endoscopists with different levels showed significantly lower diagnostic accuracy (0.410-0.580) than the AI. Prospective randomized controlled study involving 120 endoscopists into optical diagnosis of polyps with advanced features with or without AI demonstration identified that AI improved endoscopists' proportion of polyps with advanced features correctly sent for histological examination (0.960 versus 0.840, p < 0.001), and the proportion of polyps without advanced features resected and discarded (0.490 versus 0.380, p = 0.007). We thus developed an AI technique that significantly increases the accuracy of colorectal polyps with advanced features.

Indexed as

Artificial intelligenceHealth sciencesMachine learning

Identifiers

PMID38550997
PMCPMC10973580

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.