Evidence map›Paper›PMID 35999467›Full record

ArticleNPJ digital medicine2022

Development and validation of an abnormality-derived deep-learning diagnostic system for major respiratory diseases.

Chengdi Wang, Jiechao Ma, Shu Zhang, Jun Shao, Yanyan Wang, Hong-Yu Zhou, Lujia Song, Jie Zheng, Yizhou Yu, Weimin Li

Open access · goldAbstract read
In one paragraph

Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.9field-weighted citation impact, top 4% of its field
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

20 citing papers in PubMed, 34 citations in OpenAlex.

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  17. Novel tools for early diagnosis and precision treatment based on artificial intelligence.Chinese medical journal pulmonary and critical care medicine · 2023
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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

10 authors at 2 institutions in 2 countries.

Chengdi WangDepartment of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China. chengdi_wang@scu.edu.cn.
Jiechao MaAI Lab, Deepwise Healthcare, Beijing, China.
Shu ZhangAI Lab, Deepwise Healthcare, Beijing, China.ORCID http://orcid.org/0000-0002-2049-0970
Jun ShaoDepartment of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China.
Yanyan WangNursing Key Laboratory of Sichuan Province, National Clinical Research Center for Geriatrics, and Science and Technology Department, West China Hospital, Sichuan University, Chengdu, China.
Hong-Yu ZhouDepartment of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong.
Lujia SongDepartment of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China.
Jie ZhengAI Lab, Deepwise Healthcare, Beijing, China.
Yizhou YuDepartment of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong. yizhouy@acm.org.ORCID http://orcid.org/0000-0002-0470-5548
Weimin LiDepartment of Respiratory and Critical Care Medicine, Med-X Center for Manufacturing, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China. weimi003@scu.edu.cn.ORCID http://orcid.org/0000-0003-0985-0311
Sichuan University · CNUniversity of Hong Kong · HK

Funding

National Natural Science Foundation of China (National Science Foundation of China) 81871890National Natural Science Foundation of China (National Science Foundation of China) 91859203
6 · The paper itself

Abstract

Respiratory diseases impose a tremendous global health burden on large patient populations. In this study, we aimed to develop DeepMRD

Identifiers

PMID35999467
PMCPMC9395860
OpenAlexW4292707488

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.