Diagnostic Performance of Artificial Intelligence-Based Methods for Tuberculosis Detection: Systematic Review.

Hansun S, Argha A, Bakhshayeshi I, Wicaksana A, Alinejad-Rokny H, Fox GJ, Liaw ST, Celler BG, Marks GB

DOI: 10.2196/69068
Published: 2025 Mar 7
Container: Journal of medical Internet research
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.2196/69068,
  title = {Diagnostic Performance of Artificial Intelligence-Based Methods for Tuberculosis Detection: Systematic Review.},
  author = {Hansun S and Argha A and Bakhshayeshi I and Wicaksana A and Alinejad-Rokny H and Fox GJ and Liaw ST and Celler BG and Marks GB},
  year = {2025},
  journal = {Journal of medical Internet research},
  doi = {10.2196/69068},
  url = {https://doi.org/10.2196/69068}
}

RIS

TY  - JOUR
TI  - Diagnostic Performance of Artificial Intelligence-Based Methods for Tuberculosis Detection: Systematic Review.
AU  - Hansun S
AU  - Argha A
AU  - Bakhshayeshi I
AU  - Wicaksana A
AU  - Alinejad-Rokny H
AU  - Fox GJ
AU  - Liaw ST
AU  - Celler BG
AU  - Marks GB
PY  - 2025
JO  - Journal of medical Internet research
DO  - 10.2196/69068
UR  - https://doi.org/10.2196/69068
ER  -

APA

S, H., A, A., I, B., A, W., H, A., GJ, F., ST, L., BG, C., & GB, M. (2025). Diagnostic Performance of Artificial Intelligence-Based Methods for Tuberculosis Detection: Systematic Review.. Journal of medical Internet research. https://doi.org/10.2196/69068

Source records

pubmed · retrieved 2026-09-24T22:25:38.273Z
europe-pmc · retrieved 2026-09-24T22:25:38.271Z