Cite
AUTOMATED MACHINE LEARNING FRAMEWORK TO PROCESS ELECTRONIC MEDICAL RECORDS FOR CARDIOVASCULAR COMPLICATION RISK ASSESSMENT.
MLA
Lim, Chan, et al. “Automated Machine Learning Framework to Process Electronic Medical Records for Cardiovascular Complication Risk Assessment.” Journal of the American College of Cardiology (JACC), vol. 79, no. 9, Mar. 2022, p. 2017. EBSCOhost, https://doi.org/10.1016/S0735-1097(22)03008-X.
APA
Lim, C., Mekhael, M., Pottle, C., El Hajjar, A. H., Noujaim, C., Zhang, Y., & Marrouche, N. F. (2022). Automated Machine Learning Framework to Process Electronic Medical Records for Cardiovascular Complication Risk Assessment. Journal of the American College of Cardiology (JACC), 79(9), 2017. https://doi.org/10.1016/S0735-1097(22)03008-X
Chicago
Lim, Chan, Mario Mekhael, Christopher Pottle, Abdel Hadi El Hajjar, Charbel Noujaim, Yichi Zhang, and Nassir F. Marrouche. 2022. “Automated Machine Learning Framework to Process Electronic Medical Records for Cardiovascular Complication Risk Assessment.” Journal of the American College of Cardiology (JACC) 79 (9): 2017. doi:10.1016/S0735-1097(22)03008-X.