Evidence map›Paper›PMID 41550696›Full record

ArticleOpen forum infectious diseases2026

Evaluating the Usefulness of Artificial Intelligence-based Chest X-Ray Screening in Improving Tuberculosis Detection Among the High-Risk Tribal Population of Chhattisgarh, India: A Prospective Multi-Centre Study.

Abhishek Gupta, Aswathy M Nair, Shobha Ekka, Dharmendra Gahwai, Nisha Sharma, Faisal Raza Khan, Manisha Damani, Suraj Kumar, Saniya Pawar, Justy Antony Chiramal and 5 more

Abstract read
In one paragraph

Article in Open forum infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Abhishek GuptaTribal TB Initiative, Piramal Swasthya Management and Research Institute, Chhattisgarh, India.
Aswathy M NairQure.ai Technologies Pvt Ltd, Clinical, R&D, and Operational Research Division, Bengaluru, India.ORCID https://orcid.org/0000-0002-6956-4563
Shobha EkkaTribal TB Initiative, Piramal Swasthya Management and Research Institute, Chhattisgarh, India.
Dharmendra GahwaiState TB Officer, Department of Health & Family Welfare, Chhattisgarh, India.
Nisha SharmaTribal TB Initiative, Piramal Swasthya Management and Research Institute, Chhattisgarh, India.ORCID https://orcid.org/0009-0001-8809-531X
Faisal Raza KhanTribal TB Initiative, Piramal Swasthya Management and Research Institute, Chhattisgarh, India.
Manisha DamaniNational TB Elimination Programme, National Health Mission, Government of Chhattisgarh, Chhattisgarh, India.
Suraj KumarTribal TB Initiative, Piramal Swasthya Management and Research Institute, Chhattisgarh, India.
Saniya PawarQure.ai Technologies Pvt Ltd, Clinical, R&D, and Operational Research Division, Bengaluru, India.ORCID https://orcid.org/0009-0009-8110-9158
Justy Antony ChiramalQure.ai Technologies Inc., Product Division, New York City, New York, USA (Remote Work from Smyrna, Georgia, USA).ORCID https://orcid.org/0000-0002-4538-4445
Dennis RobertQure.ai Technologies Pvt Ltd, Clinical, R&D, and Operational Research Division, Bengaluru, India.ORCID https://orcid.org/0000-0002-8539-6408
Manoj TadepalliQure.ai Technologies Pvt Ltd, Clinical, R&D, and Operational Research Division, Bengaluru, India.ORCID https://orcid.org/0000-0002-8632-9231
Shibu VijayanQure.ai Technologies Pvt Ltd, Clinical, R&D, and Operational Research Division, Bengaluru, India.ORCID https://orcid.org/0000-0002-6029-2901
Pranav S KrishnanQure.ai Technologies Pvt Ltd, Clinical, R&D, and Operational Research Division, Bengaluru, India.ORCID https://orcid.org/0009-0001-7011-0833
Nidhi A PatilQure.ai Technologies Pvt Ltd, Clinical, R&D, and Operational Research Division, Bengaluru, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: India accounts for the highest Tuberculosis (TB) burden globally. The incidence and prevalence of TB are higher in tribal population than general population. In this study, we assessed the effectiveness of artificial intelligence (AI) based chest X-ray (CXR) interpretation software device (qXR version 3), in detecting TB from a predominantly tribal population setting. Methods: In this multicenter prospective study, all the CXRs of patients aged > 15 years taken for any reason at 3 public health facilities in the Chhattisgarh state of India between 01 August 2023 and 31 March 2024 were included. Patients flagged by AI as TB presumptive were directed to undergo sputum testing, who are subsequently confirmed either microbiologically or clinically. Results: Out of 2745 CXRs screened, 363 patients (median age, 44 years [IQR: 30-53]; 261 [71.9%] male) were identified as presumptive for TB. 162 cases were confirmed with TB positivity rate of 44.63% (95% CI: 39.44-49.91). Among the AI-flagged cases, 51 (14.04%) patients were asymptomatic, and 20 (39.22%) of them were confirmed with TB. Descriptively, when compared with baseline (August-2022 to March-2023), an 80.21% ( Conclusions: This study highlights the potential of AI to enhance TB detection and feasibility in a resource-limited tribal setting. Above 40% of the patients flagged by AI were subsequently confirmed to have the TB disease. Additionally, the study demonstrated the potential of AI in identifying asymptomatic individuals who would otherwise have been missed or diagnosed late.

Indexed as

analog filmsartificial intelligencechest x-raytribaltuberculosis

Identifiers

PMID41550696
PMCPMC12810203

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.