Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
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

View Full Paper
Ask AI
Bookmark
Share

Authors

RSRaju SarkarMWMedha WadhwaDPDhaval Parmar

Discussion

Loading...

Member takes

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
View Full Paper
Ask AI
Bookmark
Share

Also Consider

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

  1. 1Diagnostic accuracy of AI-assisted chest radiographs in tuberculosis screening: A Ghanaian clinical study2026 · 3 citations
  2. 2LEVERAGING AI TECHNOLOGY IN INTERPRETATION OF X-RAY IMAGES AND ITS INTEGRATION INTO THE PUBLIC HEALTH SYSTEM2026
  3. 3Artificial Intelligence for Tuberculosis Screening and Detection: From Evidence to Policy and Implementation2026 · 1 citations
  4. 4A Systematic Review of Artificial Intelligence-Assisted Chest X-Ray Interpretation for Tuberculosis Detection in Lagos Island Primary Healthcare Centres,2010
  5. 5Artificial Intelligence as an Alternative Strategy for the Rapid TB Detection, Discrimination, and Drug‐Resistance Identification: A Systematic Review and Meta‐Analysis2026