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July 12, 2026Insights into ImagingOpen Access

Development of an expert-annotated chest X-ray dataset to support AI validation in tuberculosis diagnosis

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Authors

WTWiwatana TanomkiatSTShiva Raj TimsinaTIThammasin Ingviya

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Overview

Randomized trial assesses diagnostic performance in tuberculosis, highlighting AI model validation potential.

Key Points

  • The aim is to evaluate inter-rater agreement and diagnostic performance of certified B readers in diagnosing tuberculosis from chest X-rays.
  • Analyzed 1097 chest X-rays from five institutions by six certified B readers.
  • Classified chest X-rays as unremarkable or abnormal, with a focus on tuberculosis-related abnormalities.
  • Used microbiological references for diagnosis and assessed inter-rater agreement using Fleiss’ kappa.
  • 69% of chest X-rays were abnormal and 31% were unremarkable.
  • 87% of abnormal chest X-rays were confirmed as tuberculosis by microbiological tests.
  • Sensitivity for tuberculosis findings ranged from 77.2% to 91.1%, with accuracy between 84.1% to 90.1%.

Cite This Study

Tanomkiat et al. (2026) studied this question.

synapsesocial.com/papers/6a5331ce4f7abc118adedb35https://doi.org/10.1186/s13244-026-02334-0
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Also Consider

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

  1. 1Diagnostic Accuracy of Artificial Intelligence-assisted Chest X-ray Interpretation Tools for Screening of Tuberculosis: A Systematic Review and Meta-analysis2025 · 1 citations
  2. 2The Development and Evaluation of AI-based Tuberculosis Screening with a Digital Stethoscope used to Capture Lung Sounds. A Case-Control Study.2025
  3. 3Performance 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
  4. 4Real-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
  5. 5AI X-ray for tuberculosis screening in remote Nepal: Benefits and challenges from a doctor’s perspective2025