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August 5, 2025JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCHOpen Access

Diagnostic Accuracy of Artificial Intelligence-assisted Chest X-ray Interpretation Tools for Screening of Tuberculosis: A Systematic Review and Meta-analysis

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Authors

RSRaju SarkarMWMedha WadhwaDPDhaval Parmar

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Overview

Systematic review reports 92% sensitivity and 98.2% specificity of AI-assisted chest x-ray tools for tuberculosis, indicating their potential in enhancing diagnostic accuracy.

Key Points

  • The systematic review evaluates the diagnostic accuracy of AI-assisted chest x-ray interpretation for tuberculosis.
  • Meta-analysis shows AI tools achieved an overall sensitivity of 92% and specificity of 98.2% for TB detection.
  • Authors followed PRISMA-DTA guidelines and analyzed 14 studies from a database of 1,825 records.
  • Findings indicate AI-assisted tools can significantly enhance the screening process for tuberculosis.

Cite This Study

Sarkar et al. (2025) studied this question.

synapsesocial.com/papers/689a0f99e6551bb0af8d1376https://doi.org/10.7860/jcdr/2025/79286.21293
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1AI X-ray for tuberculosis screening in remote Nepal: Benefits and challenges from a doctor’s perspective2025
  2. 2Performance of chest X-ray with computer-aided detection powered by deep learning-based artificial intelligence for tuberculosis presumptive identification during case finding in the Philippines2025 · 10 citations
  3. 3Development of an expert-annotated chest X-ray dataset to support AI validation in tuberculosis diagnosis2026
  4. 4AI-CAD enhances pulmonary TB detection and yield in active case finding2025
  5. 5Real-World Performance of AI-Powered Chest X-Ray Screening for Pulmonary Tuberculosis across County and Township Healthcare Facilities in Yichang, China, 2022-2024 (Preprint)2025