Computer-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 software

Zhi Zhen Qin; Martie van der Walt; Sizulu Moyo; Farzana Ismail; Phaleng Maribe; Claudia M. Denkinger; Sarah Zaidi; Rachael Barrett; Lindiwe Mvusi; Nkateko Mkhondo; Khangelani Zuma; Samuel Manda; Lisa Koeppel; Thuli Mthiyane; Jacob Creswell

doi:10.1016/s2589-7500(24)00118-3

July 20, 2024The Lancet Digital HealthOpen Access

Computer-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 software

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Key Points

To externally validate commercially available artificial intelligence software for computer-aided detection of tuberculosis from chest radiographs and model its diagnostic impacts.
Evaluated commercially available artificial intelligence algorithms using chest radiograph data obtained from a tuberculosis prevalence survey.
Modeled screening outcomes and diagnostic accuracy across operational triage algorithms compared with standard diagnostic workflows.
Demonstrated the external validity and feasibility of artificial intelligence software for detecting radiologic abnormalities indicative of tuberculosis.
Identified critical operational trade-offs in sensitivity and referral rates depending on software-specific triage score thresholds.

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Implication

Validation study evaluates computer-aided artificial intelligence detection of tuberculosis in a prevalence survey cohort, indicating potential utility for high-burden screening.

Abstract

Government of Canada.

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Qin et al. (2024) studied this question.

synapsesocial.com/papers/69d7c77bf39344339dd18331 https://doi.org/10.1016/s2589-7500(24)00118-3

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Computer-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 software

Key Points

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Implication

Abstract

Discussion

Cite This Study

Computer-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 software

Key Points

No abstract yet

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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