Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions.

MLA

Golumbeanu, Monica, et al. “Leveraging Mathematical Models of Disease Dynamics and Machine Learning to Improve Development of Novel Malaria Interventions.” Infectious Diseases of Poverty, vol. 11, no. 1, June 2022, pp. 1–17. EBSCOhost, https://doi.org/10.1186/s40249-022-00981-1.

APA

Golumbeanu, M., Yang, G.-J., Camponovo, F., Stuckey, E. M., Hamon, N., Mondy, M., Rees, S., Chitnis, N., Cameron, E., & Penny, M. A. (2022). Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions. Infectious Diseases of Poverty, 11(1), 1–17. https://doi.org/10.1186/s40249-022-00981-1

Chicago

Golumbeanu, Monica, Guo-Jing Yang, Flavia Camponovo, Erin M. Stuckey, Nicholas Hamon, Mathias Mondy, Sarah Rees, Nakul Chitnis, Ewan Cameron, and Melissa A. Penny. 2022. “Leveraging Mathematical Models of Disease Dynamics and Machine Learning to Improve Development of Novel Malaria Interventions.” Infectious Diseases of Poverty 11 (1): 1–17. doi:10.1186/s40249-022-00981-1.