Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments (2022)
- Authors:
- USP affiliated authors: RODRIGUES, FRANCISCO APARECIDO - ICMC ; CURY, RUBENS GISBERT - FM ; ALVES, CAROLINE LOURENÇO - ICMC ; ROSTER, KIRSTIN INGRID OLIVEIRA - ICMC ; PINEDA, ARUANE MELLO - ICMC
- Unidades: ICMC; FM
- DOI: 10.1371/journal.pone.0277257
- Subjects: REDES COMPLEXAS; APRENDIZADO COMPUTACIONAL; ELETROENCEFALOGRAFIA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: San Francisco
- Date published: 2022
- Source:
- Este periódico é de acesso aberto
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: gold
- Licença: cc-by
-
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: 28 abr. 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.0277257 -
NLM
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 abr. 28 ] Available from: https://doi.org/10.1371/journal.pone.0277257 -
Vancouver
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 abr. 28 ] Available from: https://doi.org/10.1371/journal.pone.0277257 - EEG functional connectivity and deep learning for automatic diagnosis of brain disorders: Alzheimer's disease and schizophrenia
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Informações sobre o DOI: 10.1371/journal.pone.0277257 (Fonte: oaDOI API)
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