Performance of chest X-ray with computer-aided detection powered by deep learning-based artificial intelligence for tuberculosis presumptive identification during case finding in the Philippines
Scaling up AI-CAD use in TB screening to improve TB elimination efforts could be beneficial. There is a need to calibrate threshold scores based on resource availability, prevalence, and program goals. ROC and PRC plots, which specify PPV, could serve as valuable metrics for capturing the best estimate of model performance and cost-benefit ratios within the context-specific implementation of resource-limited settings.
Authors
- Lisa Stevens (ORCID: https://orcid.org/0000-0002-6577-8812)
- Ruth Orillaza-Chi
- Erwin John T Carpio
- Mônica Maria Lins Santiago
- Jeremiah S Calderon (ORCID: https://orcid.org/0000-0001-9653-1751)
- Nuria Ponce Márquez (ORCID: https://orcid.org/0000-0002-9292-6972)
- Shawnee Shaine Salanap
Institutions
- Philippine Medical Association (PH)
- University of Makati (PH)
- UNICEF East Asia and Pacific Regional Office (TH)
- Philippine Heart Center (PH)
Publication Details
- Journal
- BMC Global and Public Health
- Published
- 2025-08-22
- DOI
- https://doi.org/10.1186/s44263-025-00198-y
- Citations
- 3
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- FHI 360