Source: PLOS ONE. Unidades: ICMC, FM
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, ELETROENCEFALOGRAFIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALVES, Caroline Lourenço et al. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLOS ONE, v. 17, n. 12, p. 1-26, 2022Tradução . . Disponível em: https://doi.org/10.1371/journal.pone.0277257. Acesso em: 26 set. 2024.APA
Alves, C. L., Cury, R. G., Roster, K., Pineda, A. M., Rodrigues, F. A., Thielemann, C., & Ciba, M. (2022). Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLOS ONE, 17( 12), 1-26. doi:10.1371/journal.pone.0277257NLM
Alves CL, Cury RG, Roster K, Pineda AM, Rodrigues FA, Thielemann C, Ciba M. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments [Internet]. PLOS ONE. 2022 ; 17( 12): 1-26.[citado 2024 set. 26 ] Available from: https://doi.org/10.1371/journal.pone.0277257Vancouver
Alves CL, Cury RG, Roster K, Pineda AM, Rodrigues FA, Thielemann C, Ciba M. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments [Internet]. PLOS ONE. 2022 ; 17( 12): 1-26.[citado 2024 set. 26 ] Available from: https://doi.org/10.1371/journal.pone.0277257