Identifying Patients at Risk of Acute Kidney Injury Among Medicare Beneficiaries With Type 2 Diabetes Initiating SGLT2 Inhibitors: A Machine Learning Approach.

MLA

Yang, Lanting, et al. “Identifying Patients at Risk of Acute Kidney Injury Among Medicare Beneficiaries With Type 2 Diabetes Initiating SGLT2 Inhibitors: A Machine Learning Approach.” Frontiers in Pharmacology, vol. 13, Mar. 2022, pp. 1–5. EBSCOhost, https://doi.org/10.3389/fphar.2022.834743.

APA

Yang, L., Gabriel, N., Hernandez, I., Vouri, S. M., Kimmel, S. E., Bian, J., & Guo, J. (2022). Identifying Patients at Risk of Acute Kidney Injury Among Medicare Beneficiaries With Type 2 Diabetes Initiating SGLT2 Inhibitors: A Machine Learning Approach. Frontiers in Pharmacology, 13, 1–5. https://doi.org/10.3389/fphar.2022.834743

Chicago

Yang, Lanting, Nico Gabriel, Inmaculada Hernandez, Scott M. Vouri, Stephen E. Kimmel, Jiang Bian, and Jingchuan Guo. 2022. “Identifying Patients at Risk of Acute Kidney Injury Among Medicare Beneficiaries With Type 2 Diabetes Initiating SGLT2 Inhibitors: A Machine Learning Approach.” Frontiers in Pharmacology 13 (March): 1–5. doi:10.3389/fphar.2022.834743.