ArticlePLOS digital health2023
Implementing a chest X-ray artificial intelligence tool to enhance tuberculosis screening in India: Lessons learned.
Article in PLOS digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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The trial behind it
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Who cites it
19 citing papers in PubMed.
- Tuberculosis disease and infection among household contacts of bacteriologically confirmed vs unconfirmed tuberculosis in Cambodia: considerations for optimising contact investigation and preventive treatment.Annals of medicine · 2026Article
- Potential to improve early detection of lung cancer through expansion of focused and opportunistic screening approaches: a scoping review focusing on potential expansion of screening risk factors and adoption of artificial intelligence models.Lung cancer management · 2026Review
- Lessons learned from implementing a large-scale contact investigation and TB preventive treatment project in India.IJTLD open · 2026Article
- Implementation of Digital Chest X-Ray with Computer-Aided Detection for Tuberculosis Screening Among Persons with Advanced HIV Disease in Maputo, Mozambique: A Retrospective Cohort Analysis.Diagnostics (Basel, Switzerland) · 2026Article
- Dissemination and implementation science for global ophthalmology: closing the last-mile translational gap.Frontiers in public health · 2026Review
- Accuracy and operational performance of computer-aided detection software use cases for TB screening: a retrospective comparative evaluation in Ho Chi Minh City, Viet Nam.BMJ public health · 2026Article
- Resources to implement general population mobile chest x-ray screening for tuberculosis in Uganda: A trial-based costing analysis.PLOS global public health · 2026Article
- Evaluating the Usefulness of Artificial Intelligence-based Chest X-Ray Screening in Improving Tuberculosis Detection Among the High-Risk Tribal Population of Chhattisgarh, India: A Prospective Multi-Centre Study.Open forum infectious diseases · 2026Article
- Review
- Leveraging artificial intelligence policy for inclusive and sustainable youth entrepreneurship: micro evidence from China.Frontiers in public health · 2026Article
- The role of chest X-ray in tuberculosis detection for high school students in China: a cross-sectional study.Scientific reports · 2025Article
- Personnel time requirements for mobile chest X-ray screening for TB.IJTLD open · 2025Article
- Article
- Integration of AI and ML in Tuberculosis (TB) Management: From Diagnosis to Drug Discovery.Diseases (Basel, Switzerland) · 2025Review
- Comparison of different Lunit INSIGHT CXR software versions when reading chest radiographs for tuberculosis.PLOS digital health · 2025Article
- Active case-finding for TB in India: Assessment of scale and quality benchmarks, time taken and use of rapid molecular diagnostic tests.PLOS global public health · 2025Article
- Comparing the Output of an Artificial Intelligence Algorithm in Detecting Radiological Signs of Pulmonary Tuberculosis in Digital Chest X-Rays and Their Smartphone-Captured Photos of X-Ray Films: Retrospective Study.JMIR formative research · 2024Article
- A mixed-methods study on impact of active case finding on pulmonary tuberculosis treatment outcomes in India.Archives of public health = Archives belges de sante publique · 2024Article
- TubIAgnosis: A machine learning-based web application for active tuberculosis diagnosis using complete blood count data.Digital healthArticle
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Artificial Intelligence (AI) based chest X-ray (CXR) screening for tuberculosis (TB) is becoming increasingly popular. Still, deploying such AI tools can be challenging due to multiple real-life barriers like software installation, workflow integration, network connectivity constraints, limited human resources available to interpret findings, etc. To understand these challenges, PATH implemented a TB REACH active case-finding program in a resource-limited setting of Nagpur in India, where an AI software device (qXR) intended for TB screening using CXR images was used. Eight private CXR laboratories that fulfilled prerequisites for AI software installation were engaged for this program. Key lessons about operational feasibility and accessibility, along with the strategies adopted to overcome these challenges, were learned during this program. This program also helped to screen 10,481 presumptive TB individuals using informal providers based on clinical history. Among them, 2,303 individuals were flagged as presumptive for TB by a radiologist or by AI based on their CXR interpretation. Approximately 15.8% increase in overall TB yield could be attributed to the presence of AI alone because these additional cases were not deemed presumptive for TB by radiologists, but AI was able to identify them. Successful implementation of AI tools like qXR in resource-limited settings in India will require solving real-life implementation challenges for seamless deployment and workflow integration.
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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.