APA (7th ed.) Citation

van Veen, R., Meles, S. K., Renken, R. J., Reesink, F. E., Oertel, W. H., Janzen, A., . . . Biehl, M. (2022). FDG-PET combined with learning vector quantization allows classification of neurodegenerative diseases and reveals the trajectory of idiopathic REM sleep behavior disorder. Computer methods and programs in biomedicine, 225, 107042. https://doi.org/10.1016/j.cmpb.2022.107042

Chicago Style (17th ed.) Citation

van Veen, Rick, Sanne K. Meles, Remco J. Renken, Fransje E. Reesink, Wolfgang H. Oertel, Annette Janzen, Gert-Jan de Vries, Klaus L. Leenders, and Michael Biehl. "FDG-PET Combined with Learning Vector Quantization Allows Classification of Neurodegenerative Diseases and Reveals the Trajectory of Idiopathic REM Sleep Behavior Disorder." Computer Methods and Programs in Biomedicine 225 (2022): 107042. https://doi.org/10.1016/j.cmpb.2022.107042.

MLA (9th ed.) Citation

van Veen, Rick, et al. "FDG-PET Combined with Learning Vector Quantization Allows Classification of Neurodegenerative Diseases and Reveals the Trajectory of Idiopathic REM Sleep Behavior Disorder." Computer Methods and Programs in Biomedicine, vol. 225, 2022, p. 107042, https://doi.org/10.1016/j.cmpb.2022.107042.