A Random Forest Based Risk Model for Reliable and Accurate Prediction of Receipt of Transfusion in Patients Undergoing Percutaneous Coronary Intervention.

MLA

Gurm, Hitinder S., et al. “A Random Forest Based Risk Model for Reliable and Accurate Prediction of Receipt of Transfusion in Patients Undergoing Percutaneous Coronary Intervention.” PLoS ONE, vol. 9, no. 5, May 2014, pp. 1–9. EBSCOhost, https://doi.org/10.1371/journal.pone.0096385.

APA

Gurm, H. S., Kooiman, J., LaLonde, T., Grines, C., Share, D., & Seth, M. (2014). A Random Forest Based Risk Model for Reliable and Accurate Prediction of Receipt of Transfusion in Patients Undergoing Percutaneous Coronary Intervention. PLoS ONE, 9(5), 1–9. https://doi.org/10.1371/journal.pone.0096385

Chicago

Gurm, Hitinder S., Judith Kooiman, Thomas LaLonde, Cindy Grines, David Share, and Milan Seth. 2014. “A Random Forest Based Risk Model for Reliable and Accurate Prediction of Receipt of Transfusion in Patients Undergoing Percutaneous Coronary Intervention.” PLoS ONE 9 (5): 1–9. doi:10.1371/journal.pone.0096385.