APA

Massie, A. B., Boyarsky, B. J., Werbel, W. A., Bae, S., Chow, E. K. H., Avery, R. K., Durand, C. M., Desai, N., Brennan, D., Garonzik-Wang, J. M., & Segev, D. L. (2020). Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study. American Journal of Transplantation, 20(11), 2997. https://doi.org/10.1111/ajt.16117

CHICAGO

Massie, Allan B., Brian J. Boyarsky, William A. Werbel, Sunjae Bae, Eric K. H. Chow, Robin K. Avery, Christine M. Durand, et al. 2020. “Identifying Scenarios of Benefit or Harm from Kidney Transplantation during the COVID-19 Pandemic: A Stochastic Simulation and Machine Learning Study.” American Journal of Transplantation 20 (11): 2997. doi:10.1111/ajt.16117.

HARVARD

Massie, A. B. et al. (2020) ‘Identifying scenarios of benefit or harm from kidney transplantation during the COVID-19 pandemic: A stochastic simulation and machine learning study’, American Journal of Transplantation, 20(11), p. 2997. doi: 10.1111/ajt.16117.

MLA

Massie, Allan B., et al. “Identifying Scenarios of Benefit or Harm from Kidney Transplantation during the COVID-19 Pandemic: A Stochastic Simulation and Machine Learning Study.” American Journal of Transplantation, vol. 20, no. 11, Nov. 2020, p. 2997., doi:10.1111/ajt.16117.

TURABIAN

Massie, Allan B., Brian J. Boyarsky, William A. Werbel, Sunjae Bae, Eric K. H. Chow, Robin K. Avery, Christine M. Durand, et al. “Identifying Scenarios of Benefit or Harm from Kidney Transplantation during the COVID-19 Pandemic: A Stochastic Simulation and Machine Learning Study.” American Journal of Transplantation 20, no. 11 (November 1, 2020): 2997. doi:10.1111/ajt.16117.