ArticleScientific reports2018
Evaluation of the diagnostic accuracy of Computer-Aided Detection of tuberculosis on Chest radiography among private sector patients in Pakistan.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 4 of them syntheses that pooled it.
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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.
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.
Who cites it
30 citing papers in PubMed, 4 syntheses or guidelines pooled it, 71 citations in OpenAlex.
- Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review.Journal of medical Internet research · 2023Pooled it
- Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years Review.Journal of medical systems · 2022Pooled it
- Chest X-ray Analysis With Deep Learning-Based Software as a Triage Test for Pulmonary Tuberculosis: An Individual Patient Data Meta-Analysis of Diagnostic Accuracy.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022Pooled it
- Pooled it
- Mapping respiratory health digital interventions in South and Southeast Asia: a scoping review.Journal of global health · 2025Article
- Detection of pulmonary tuberculosis through mobile X-ray based active case-finding in Pakistan: a retrospective analysis from programmatic screening of1 214 289 individuals from 2017 to 2021.BMJ global health · 2025Article
- A systematic review and meta-analysis of artificial intelligence software for tuberculosis diagnosis using chest X-ray imaging.Journal of thoracic disease · 2025Article
- Article
- Geographical targeting of active case finding for tuberculosis in Pakistan using hotspots identified by artificial intelligence software (SPOT-TB): study protocol for a pragmatic stepped wedge cluster randomised control trial.BMJ open respiratory research · 2024Article
- Impact of the private sector on spatial accessibility to chest radiography services in Lima, Peru.IJTLD open · 2024Article
- Iterative evaluation of mobile computer-assisted digital chest x-ray screening for TB improves efficiency, yield, and outcomes in Nigeria.PLOS global public health · 2024Article
- Computer-aided detection thresholds for digital chest radiography interpretation in tuberculosis diagnostic algorithms.ERJ open research · 2024Article
- Early user perspectives on using computer-aided detection software for interpreting chest X-ray images to enhance access and quality of care for persons with tuberculosis.BMC global and public health · 2023Review
- Comparing tuberculosis symptom screening to chest X-ray with artificial intelligence in an active case finding campaign in Northeast Nigeria.BMC global and public health · 2023Article
- Review on chest pathogies detection systems using deep learning techniques.Artificial intelligence review · 2023Article
- The Performance of Computer-Aided Detection Digital Chest X-ray Reading Technologies for Triage of Active Tuberculosis Among Persons With a History of Previous Tuberculosis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- CAD4TB software updates: different triaging thresholds require caution by users and regulation by authorities.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2023Article
- A spatial analysis of TB cases and abnormal X-rays detected through active case-finding in Karachi, Pakistan.Scientific reports · 2023Article
- Computer-aided diagnostic accuracy of pulmonary tuberculosis on chest radiography among lower respiratory tract symptoms patients.Frontiers in public health · 2023Article
- Diagnostic Accuracy of the Artificial Intelligence Methods in Medical Imaging for Pulmonary Tuberculosis: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2022Review
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 5 countries.
Funding
Abstract
The introduction of digital CXR with automated computer-aided interpretation, has given impetus to the role of CXR in TB screening, particularly in low resource, high-burden settings. The aim of this study was to evaluate the diagnostic accuracy of CAD4TB as a screening tool, implemented in the private sector in Karachi, Pakistan. This study analyzed retrospective data from CAD4TB and Xpert MTB/RIF testing carried out at two private TB treatment and diagnostic centers in Karachi. Sensitivity, specificity, potential Xperts saved, were computed and the receiver operator characteristic curves were constructed for four different models of CAD4TB. A total of 6,845 individuals with presumptive TB were enrolled in the study, 15.2% of which had MTB + ve result on Xpert. A high sensitivity (range 65.8-97.3%) and NPV (range 93.1-98.4%) were recorded for CAD4TB. The Area under the ROC curve (AUC) for CAD4TB was 0.79. CAD4TB with patient demographics (age and gender) gave an AUC of 0.83. CAD4TB offered high diagnostic accuracy. In low resource settings, CAD4TB, as a triage tool could minimize use of Xpert. Using CAD4TB in combination with age and gender data enhanced the performance of the software. Variations in demographic information generate different individual risk probabilities for the same CAD4TB scores.
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Registered trials
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.