Evidence map›Paper›PMID 41089228›Full record

ArticleIJTLD open2025

AI-CAD enhances pulmonary TB detection and yield in active case finding.

A Frederick, R Kubendiran, T Neelagandan, K K Shankar, A Ojha, R Pant, S Pardeshi, T Gupte, A Kharat

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Article in IJTLD open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

A FrederickDepartment of Health and Family Welfare, Chennai, India.
R KubendiranDepartment of Health and Family Welfare, Chennai, India.
T NeelagandanDepartment of Health and Family Welfare, Chennai, India.
K K ShankarDepartment of Health and Family Welfare, Chennai, India.
A OjhaDeepTek Medical Imaging Pvt. Ltd., Pune, India.
R PantDeepTek Medical Imaging Pvt. Ltd., Pune, India.
S PardeshiDeepTek Medical Imaging Pvt. Ltd., Pune, India.
T GupteDeepTek Medical Imaging Pvt. Ltd., Pune, India.
A KharatDeepTek Medical Imaging Pvt. Ltd., Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIndia accounts for 27% of global TB incidence and bears the highest TB burden worldwide. This study evaluates the performance of an AI-assisted computer-aided detection (AI-CAD) solution in a community-based, active case-finding TB screening programme conducted in Tamil Nadu, India. It also provides a comparative analysis of AI-assisted screening and conventional screening methods.

methodsCommunity-based TB screening was carried out using mobile diagnostic units equipped with digital X-ray machines. The performance of the AI-CAD solution was evaluated by calculating area under the receiver operating characteristic (AUROC) curve, sensitivity, and specificity. Additionally, data from five districts that used conventional screening methods were analysed for comparative analysis against AI-assisted screening.

resultsAI-CAD exceeded the World Health Organization (WHO)-recommended minimum target product profile (TPP) with a sensitivity of 0.93 (95% confidence interval [CI]: 0.88, 0.97) and a specificity of 0.83 (95% CI: 0.82, 0.83). AI interpretation was significantly associated with positive TB diagnosis (odds ratio: 58.95,

conclusionThe AI-CAD met and exceeded the WHO's minimal TPP for TB detection. The higher sputum-positive yield reinforces AI-CAD's potential in large-scale TB screening programmes.

Indexed as

artificial intelligencechest X-raycomputer-aided detectionIndiaTamil Nadutuberculosis

Identifiers

PMID41089228
PMCPMC12517255

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