Creswell, Jacob

Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems

Qin, Z. Z., Sander, M. S., Rai, B., Titahong, C. N., Sudrungrot, S., Laah, S. N., Adhikari, L. M., Carter, E. J., Puri, L., Codlin, A. J., et al. (2019) · Scientific Reports

COVID-19 diagnosis using AITuberculosis Research and Epidemiology

Cited by 289

Engaging the private sector to increase tuberculosis case detection: an impact evaluation study

Khan, A. J., Khowaja, S., Khan, F. S., Qazi, F., Lotia, I., Habib, A., Mohammed, S., Khan, U., Amanullah, F., Hussain, H., et al. (2012) · The Lancet Infectious Diseases

Tuberculosis Research and EpidemiologyHealthcare Systems and Reforms

Cited by 136

An evaluation of automated chest radiography reading software for tuberculosis screening among public- and private-sector patients

Rahman, M. T., Codlin, A. J., Rahman, M. M., Nahar, A., Reja, M., Islam, T., Qin, Z. Z., Khan, M. A. S., Banu, S., & Creswell, J. (2017) · European Respiratory Journal

Tuberculosis Research and EpidemiologyCOVID-19 diagnosis using AI

Cited by 66

Improving tuberculosis case detection in children: summary of innovations and findings from 18 countries

Rahman, M. T., Malik, A. A., Amanullah, F., & Creswell, J. (2022) · Journal of the Pediatric Infectious Diseases Society

Tuberculosis Research and EpidemiologyDiagnosis and treatment of tuberculosis

Cited by 10

Impact of intensified tuberculosis case finding at health facilities on case notifications in Cameroon: a controlled interrupted time series analysis

Adamou Mana, Z., Beaudou, C. N., Hilaire, K. F. J., Konso, J., Ndahbove, C., Waindim, Y., Ganava, M., Malama, T., Matip, C., Meoto, P., et al. (2022) · PLOS Global Public Health

Tuberculosis Research and EpidemiologyInfectious Diseases and Tuberculosis

Cited by 5