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May 24, 2026Open Access

Computer-aided detection thresholds for digital chest x-ray interpretation in tuberculosis diagnostic algorithms

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HCHuman Sciences Research Council

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Overview

Randomized trial determines computer-aided detection thresholds in tuberculosis diagnostic algorithms, suggesting improved screening accuracy.

Key Points

  • The aim is to establish effective thresholds for computer-aided detection in tuberculosis screening when comprehensive reference testing is lacking.
  • Secondary analysis of data from the 2019 Lesotho national tuberculosis prevalence survey.
  • Evaluation of computer-aided detection software performance in identifying tuberculosis cases.
  • Specific thresholds were identified that optimize the sensitivity and specificity for tuberculosis detection.
  • Results indicate improved predictive accuracy for computer-aided detection when applied to chest x-rays.

Cite This Study

Human Sciences Research Council (2026) studied this question.

synapsesocial.com/papers/6a1295ce48a0ea166567220bhttps://doi.org/10.14749/32362248
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Also Consider

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

  1. 1Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software2026
  2. 2Incidental radiological findings during clinical tuberculosis screening in Lesotho and South Africa: a case series2026
  3. 3A multi-country head-to-head accuracy comparison of automated chest x-ray algorithms for tuberculosis2026
  4. 4Computer-aided detection of TB from chest radiographs in a TB prevalence survey: external validation and modelled impacts of commercially available artificial intelligence software2025
  5. 5Implementation of Digital Chest X-Ray with Computer-Aided Detection for Tuberculosis Screening Among Persons with Advanced HIV Disease in Maputo, Mozambique: A Retrospective Cohort Analysis2026