Cita APA (7a ed.)
Haque, A., Stubbs, D., Hubig, N. C., Spinale, F. G., & Richardson, W. J. (2022). Interpretable machine learning predicts cardiac resynchronization therapy responses from personalized biochemical and biomechanical features. BMC Medical Informatics & Decision Making, 22(1), 1-11.
Cita Chicago Style (17a ed.)
Haque, Anamul, Doug Stubbs, Nina C. Hubig, Francis G. Spinale, y William J. Richardson. "Interpretable Machine Learning Predicts Cardiac Resynchronization Therapy Responses from Personalized Biochemical and Biomechanical Features." BMC Medical Informatics & Decision Making 22, no. 1 (2022): 1-11.
Cita MLA (9a ed.)
Haque, Anamul, et al. "Interpretable Machine Learning Predicts Cardiac Resynchronization Therapy Responses from Personalized Biochemical and Biomechanical Features." BMC Medical Informatics & Decision Making, vol. 22, no. 1, 2022, pp. 1-11.
Precaución: Estas citas no son 100% exactas.