Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage
Using CAD scores in multivariable models outperformed the current practice of CAD-threshold-based CXR classification for TB diagnosis.
Authors
- Monde Muyoyeta (ORCID: https://orcid.org/0000-0003-3609-5403)
- Faiz Ahmad Khan (ORCID: https://orcid.org/0000-0003-0473-8734)
- Mary Kagujje (ORCID: https://orcid.org/0000-0003-4818-6548)
- Aamir Khan (ORCID: https://orcid.org/0000-0001-8431-2498)
- Marianne Breuninger
- Keertan Dheda (ORCID: https://orcid.org/0000-0001-7709-5341)
- Gamuchirai Tavaziva
- Coralie Geric
- Alex Scott (ORCID: https://orcid.org/0000-0003-0647-607X)
- Klaus Reither (ORCID: https://orcid.org/0000-0001-6195-8237)
- Andrea Benedetti (ORCID: https://orcid.org/0000-0002-8314-9497)
- Ali Esmail
Institutions
- Centre for Infectious Disease Research in Zambia (ZM)
- University of Cape Town (ZA)
- Swiss Tropical and Public Health Institute (CH)
- University of Cologne (DE)
- McGill University Health Centre (CA)
- London School of Hygiene & Tropical Medicine (GB)
Publication Details
- Journal
- International Journal of Infectious Diseases
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1016/j.ijid.2024.107221
- Citations
- 3
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- Fonds de Recherche du Québec-Société et Culture