A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling.

MLA

Leger, Stefan, et al. “A Comparative Study of Machine Learning Methods for Time-to-Event Survival Data for Radiomics Risk Modelling.” Scientific Reports, vol. 7, no. 1, Oct. 2017, p. 13206. EBSCOhost, https://doi.org/10.1038/s41598-017-13448-3.

APA

Leger, S., Zwanenburg, A., Pilz, K., Lohaus, F., Linge, A., Zöphel, K., Kotzerke, J., Schreiber, A., Tinhofer, I., Budach, V., Sak, A., Stuschke, M., Balermpas, P., Rödel, C., Ganswindt, U., Belka, C., Pigorsch, S., Combs, S. E., Mönnich, D., … Richter, C. (2017). A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling. Scientific Reports, 7(1), 13206. https://doi.org/10.1038/s41598-017-13448-3

Chicago

Leger, Stefan, Alex Zwanenburg, Karoline Pilz, Fabian Lohaus, Annett Linge, Klaus Zöphel, Jörg Kotzerke, et al. 2017. “A Comparative Study of Machine Learning Methods for Time-to-Event Survival Data for Radiomics Risk Modelling.” Scientific Reports 7 (1): 13206. doi:10.1038/s41598-017-13448-3.