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February 11, 2026Open Access

A Systematic Review of Artificial Intelligence-Assisted Chest Radiography for Tuberculosis Case Detection in Primary Health Centres of Maputo Province, Mozambique

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Authors

AMAna Paula MacuácuaCMCarlos MunguambeINIsabel Nhantumbo

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Overview

A systematic review evaluates AI's diagnostic performance for tuberculosis in primary health centres, suggesting effective implementation strategies.

Key Points

  • This review assesses the effectiveness and challenges of using AI-assisted chest radiography for tuberculosis detection in Maputo's primary health centres.
  • Systematic search of electronic databases for relevant studies.
  • Inclusion of peer-reviewed articles, reports, and conference proceedings.
  • Screening studies against predefined eligibility criteria for data extraction.
  • AI algorithms showed high sensitivity over 90% for detecting pulmonary tuberculosis.
  • Specificity varied among studies and is less consistently high.
  • Integration into clinical workflows and stable digital infrastructure are critical for success.

Cite This Study

Macuácua et al. (2016) studied this question.

synapsesocial.com/papers/698c1c53267fb587c655eaf8https://doi.org/10.5281/zenodo.18530933
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Also Consider

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

  1. 1A Systematic Review of Artificial Intelligence-Assisted Chest X-Ray Interpretation for Tuberculosis Detection in Lagos Island Primary Healthcare Centres,2010
  2. 2Artificial Intelligence-Assisted chest X-ray for tuberculosis case finding in low- and Middle-Income countries: Implementation experiences and impact2026
  3. 3Artificial Intelligence for Tuberculosis Screening and Detection: From Evidence to Policy and Implementation2026 · 1 citations
  4. 4Impact of a digital chest X-ray and artificial intelligence campaign on pulmonary tuberculosis case detection in a Malawian prison, 20132013
  5. 5Diagnostic accuracy of AI-assisted chest radiographs in tuberculosis screening: A Ghanaian clinical study2026 · 3 citations