Alves, Caroline Lourenço 
; Cury, Rubens Gisbert ; Roster, Kirstin ; Pineda, Aruane Mello ; Rodrigues, Francisco Aparecido ; Thielemann, Christiane ; Ciba, Manuel
Source: PLoS ONE. Unidades: ICMC, FM
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, ELETROENCEFALOGRAFIA
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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: 27 nov. 2025.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 2025 nov. 27 ] 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 2025 nov. 27 ] Available from: https://doi.org/10.1371/journal.pone.0277257
