Sociodemographic Indicators of Health Status Using a Machine Learning Approach and Data from the English Longitudinal Study of Aging (ELSA).

MLA

Engchuan, Worrawat, et al. “Sociodemographic Indicators of Health Status Using a Machine Learning Approach and Data from the English Longitudinal Study of Aging (ELSA).” Medical Science Monitor : International Medical Journal of Experimental and Clinical Research, vol. 25, Mar. 2019, pp. 1994–2001. EBSCOhost, https://doi.org/10.12659/MSM.913283.

APA

Engchuan, W., Dimopoulos, A. C., Tyrovolas, S., Caballero, F. F., Sanchez-Niubo, A., Arndt, H., Ayuso-Mateos, J. L., Haro, J. M., Chatterji, S., & Panagiotakos, D. B. (2019). Sociodemographic Indicators of Health Status Using a Machine Learning Approach and Data from the English Longitudinal Study of Aging (ELSA). Medical Science Monitor : International Medical Journal of Experimental and Clinical Research, 25, 1994–2001. https://doi.org/10.12659/MSM.913283

Chicago

Engchuan, Worrawat, Alexandros C Dimopoulos, Stefanos Tyrovolas, Francisco Félix Caballero, Albert Sanchez-Niubo, Holger Arndt, Jose Luis Ayuso-Mateos, Josep Maria Haro, Somnath Chatterji, and Demosthenes B Panagiotakos. 2019. “Sociodemographic Indicators of Health Status Using a Machine Learning Approach and Data from the English Longitudinal Study of Aging (ELSA).” Medical Science Monitor : International Medical Journal of Experimental and Clinical Research 25 (March): 1994–2001. doi:10.12659/MSM.913283.