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
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.
Authors
- Manisha Damani
- Faisal Raza Khan
- Ashalatha S. Nair (ORCID: https://orcid.org/0000-0001-6369-9160)
- Dharmendra Gahwai
- Justy Antony Chiramal (ORCID: https://orcid.org/0000-0002-4538-4445)
- Nidhi Patil
- Shobha Ekka
- Suraj Kumar (ORCID: https://orcid.org/0000-0003-3724-3770)
- Saniya Pawar
- Abhishek Gupta
- Nisha Sharma
- Manoj Tadepalli
- Dennis Robert
- Pranav S Krishnan
- Shibu Vijayan
Institutions
- Qualcomm (United Kingdom) (GB)
- Department of Health & Family Welfare (IN)
- National Institute for Research in Tribal Health (IN)
- Center For Remote Sensing (United States) (US)
- Directorate of Health and Family Welfare Government of Chhattisgarh (IN)
Publication Details
- Journal
- Open Forum Infectious Diseases
- Published
- 2025-12-26
- DOI
- https://doi.org/10.1093/ofid/ofaf780
- Primary Topic
- Tuberculosis Research and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00