Cite
AKIMLpred: An interpretable machine learning model for predicting acute kidney injury within seven days in critically ill patients based on a prospective cohort study.
MLA
Sun, Tao, et al. “AKIMLpred: An Interpretable Machine Learning Model for Predicting Acute Kidney Injury within Seven Days in Critically Ill Patients Based on a Prospective Cohort Study.” Clinica Chimica Acta, vol. 559, June 2024, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.cca.2024.119705.
APA
Sun, T., Yue, X., Zhang, G., Lin, Q., Chen, X., Huang, T., Li, X., Liu, W., & Tao, Z. (2024). AKIMLpred: An interpretable machine learning model for predicting acute kidney injury within seven days in critically ill patients based on a prospective cohort study. Clinica Chimica Acta, 559, N.PAG. https://doi.org/10.1016/j.cca.2024.119705
Chicago
Sun, Tao, Xiaofang Yue, Gong Zhang, Qinyan Lin, Xiao Chen, Tiancha Huang, Xiang Li, Weiwei Liu, and Zhihua Tao. 2024. “AKIMLpred: An Interpretable Machine Learning Model for Predicting Acute Kidney Injury within Seven Days in Critically Ill Patients Based on a Prospective Cohort Study.” Clinica Chimica Acta 559 (June): N.PAG. doi:10.1016/j.cca.2024.119705.