Prediction of Length of Stay in the Emergency Department for COVID-19 Patients: A Machine Learning Approach

MLA

Egbe-Etu Etu, et al. “Prediction of Length of Stay in the Emergency Department for COVID-19 Patients: A Machine Learning Approach.” IEEE Access, vol. 10, Jan. 2022, pp. 42243–51. EBSCOhost, https://doi.org/10.1109/ACCESS.2022.3168045.

APA

Egbe-Etu Etu, Leslie Monplaisir, Suzan Arslanturk, Sara Masoud, Celestine Aguwa, Ihor Markevych, & Joseph Miller. (2022). Prediction of Length of Stay in the Emergency Department for COVID-19 Patients: A Machine Learning Approach. IEEE Access, 10, 42243–42251. https://doi.org/10.1109/ACCESS.2022.3168045

Chicago

Egbe-Etu Etu, Leslie Monplaisir, Suzan Arslanturk, Sara Masoud, Celestine Aguwa, Ihor Markevych, and Joseph Miller. 2022. “Prediction of Length of Stay in the Emergency Department for COVID-19 Patients: A Machine Learning Approach.” IEEE Access 10 (January): 42243–51. doi:10.1109/ACCESS.2022.3168045.