Evidence map›Paper›PMID 40486951›Full record

ArticleChronic diseases and translational medicine2025

Performance of Computer-Aided Detection Software in Tuberculosis Case Finding in Township Health Centers in China.

Xuefang Cao, Boxuan Feng, Bin Zhang, Dakuan Wang, Jiang Du, Yijun He, Tonglei Guo, Shouguo Pan, Zisen Liu, Jiaoxia Yan and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Chronic diseases and translational medicine, 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. 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

13 authors.

Xuefang CaoNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Boxuan FengNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Bin ZhangCenter for Disease Control and Prevention of Zhongmu County Zhengzhou Henan China.
Dakuan WangCenter for Disease Control and Prevention of Zhongmu County Zhengzhou Henan China.
Jiang DuNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Yijun HeNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Tonglei GuoNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Shouguo PanCenter for Disease Control and Prevention of Zhongmu County Zhengzhou Henan China.
Zisen LiuCenter for Disease Control and Prevention of Zhongmu County Zhengzhou Henan China.
Jiaoxia YanCenter for Disease Control and Prevention of Zhongmu County Zhengzhou Henan China.
Qi JinNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.
Lei GaoNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.ORCID 0000-0002-9957-4527
Henan XinNHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Computer-aided detection (CAD) software has been introduced to automatically interpret digital chest X-rays. This study aimed to evaluate the performance of CAD software (JF CXR-1 v3.0, which was developed by a domestic Hi-tech enterprise) in tuberculosis (TB) case finding in China. Methods: In 2019, we conducted an internal evaluation of the performance of JF CXR-1 v3.0 by reading standard images annotated by a panel of experts. In 2020, using the reading results of chest X-rays by a panel of experts as the reference standard, we conducted an on-site prospective study to evaluate the performance of JF CXR-1 v3.0 and local radiologists in TB case finding in 13 township health centers in Zhongmu County, Henan Province. Results: Internal assessment results based on 277 standard images showed that JF CXR-1 v3.0 had a sensitivity of 85.94% (95% confidence interval [CI]: 77.42%, 94.45%) and a specificity of 74.65% (95% CI: 68.81%, 80.49%) to distinguish active TB from other imaging conditions. In the on-site evaluation phase, images from 3705 outpatients who underwent chest X-ray detection were read by JF CXR-1 v3.0 and local radiologists in parallel. The imaging diagnosis of local radiologists for active TB had a sensitivity of 32.89% (95% CI: 22.33%, 43.46%) and a specificity of 99.28% (95% CI: 99.01%, 99.56%), while JF CXR-1 v3.0 showed a significantly higher sensitivity of 92.11% (95% CI: 86.04%, 98.17%) ( Conclusions: CAD software could play a positive role in improving the TB case finding capability of township health centers.

Indexed as

artificial intelligencecase findingchest X‐raycomputer‐aided detectiontuberculosis

Identifiers

PMID40486951
PMCPMC12142701

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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.