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Artigo de periodico
On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments (2024)
Alves, Caroline Lourenço ; Ciba, Manuel ; Toutain, Thaise Graziele Lima de ; Porto, Joel Augusto Moura ; Sena, Eduardo Pondé de ; Thielemann, Christiane ; Rodrigues, Francisco
Fonte: Journal of Physics: Complexity. Unidades: ICMC, IFSC
Assuntos: VISÃO COMPUTACIONAL, APRENDIZADO COMPUTACIONAL, TOPOLOGIA EM COMPUTAÇÃO, REDES NEURAIS, TEORIA DOS GRAFOS, CÓRTEX CEREBRAL (ANÁLISE), CÉREBRO (ANÁLISE;ESTUDO)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALVES, Caroline Lourenço et al. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, v. 5, n. Ja 2024, p. 015002-1-015002-23, 2024Tradução . . Disponível em: https://doi.org/10.1088/2632-072X/ad1c68. Acesso em: 05 jun. 2024.
APA
Alves, C. L., Ciba, M., Toutain, T. G. L. de, Porto, J. A. M., Sena, E. P. de, Thielemann, C., & Rodrigues, F. (2024). On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments. Journal of Physics: Complexity, 5( Ja 2024), 015002-1-015002-23. doi:10.1088/2632-072X/ad1c68
NLM
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68
Vancouver
Alves CL, Ciba M, Toutain TGL de, Porto JAM, Sena EP de, Thielemann C, Rodrigues F. On the advances in machine learning and complex network measures to an EEG dataset from DMT experiments [Internet]. Journal of Physics: Complexity. 2024 ; 5( Ja 2024): 015002-1-015002-23.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1088/2632-072X/ad1c68
Artigo de periodico
Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning (2023)
Pineda, Aruane Mello ; Rodrigues, Francisco Aparecido ; Alves, Caroline Lourenço ; Möckel, Michael; Oliveira, Thaise Graziele Lima de ; Porto, Joel Augusto Moura
Fonte: Journal of Complex Networks. Unidades: ICMC, IFSC
Assuntos: TECNOLOGIAS DA SAÚDE, APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, DOENÇAS VASCULARES
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PINEDA, Aruane Mello et al. Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning. Journal of Complex Networks, v. 11, n. 5, p. cnad030-1-cnad030-21, 2023Tradução . . Disponível em: https://doi.org/10.1093/comnet/cnad030. Acesso em: 05 jun. 2024.
APA
Pineda, A. M., Rodrigues, F. A., Alves, C. L., Möckel, M., Oliveira, T. G. L. de, & Porto, J. A. M. (2023). Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning. Journal of Complex Networks, 11( 5), cnad030-1-cnad030-21. doi:10.1093/comnet/cnad030
NLM
Pineda AM, Rodrigues FA, Alves CL, Möckel M, Oliveira TGL de, Porto JAM. Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning [Internet]. Journal of Complex Networks. 2023 ; 11( 5): cnad030-1-cnad030-21.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1093/comnet/cnad030
Vancouver
Pineda AM, Rodrigues FA, Alves CL, Möckel M, Oliveira TGL de, Porto JAM. Analysis of quantile graphs in EGC data from elderly and young individuals using machine learning and deep learning [Internet]. Journal of Complex Networks. 2023 ; 11( 5): cnad030-1-cnad030-21.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1093/comnet/cnad030
Artigo de periodico
Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia (2023)
Alves, Caroline Lourenço ; Oliveira, Thaise Graziele Lima de ; Porto, Joel Augusto Moura ; Aguiar, Patricia Maria de Carvalho ; Sena, Eduardo Pondé de ; Rodrigues, Francisco Aparecido ; Pineda, Aruane Mello ; Thielemann, Christiane
Fonte: Journal of Neural Engineering. Unidades: ICMC, IFSC
Assuntos: TECNOLOGIAS DA SAÚDE, APRENDIZADO COMPUTACIONAL, ESQUIZOFRENIA, REDES COMPLEXAS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, CÉREBRO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALVES, Caroline Lourenço et al. Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia. Journal of Neural Engineering, v. 20, n. 5, p. 056025-1-056025-28, 2023Tradução . . Disponível em: https://doi.org/10.1088/1741-2552/acf734. Acesso em: 05 jun. 2024.
APA
Alves, C. L., Oliveira, T. G. L. de, Porto, J. A. M., Aguiar, P. M. de C., Sena, E. P. de, Rodrigues, F. A., et al. (2023). Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia. Journal of Neural Engineering, 20( 5), 056025-1-056025-28. doi:10.1088/1741-2552/acf734
NLM
Alves CL, Oliveira TGL de, Porto JAM, Aguiar PM de C, Sena EP de, Rodrigues FA, Pineda AM, Thielemann C. Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia [Internet]. Journal of Neural Engineering. 2023 ; 20( 5): 056025-1-056025-28.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1088/1741-2552/acf734
Vancouver
Alves CL, Oliveira TGL de, Porto JAM, Aguiar PM de C, Sena EP de, Rodrigues FA, Pineda AM, Thielemann C. Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia [Internet]. Journal of Neural Engineering. 2023 ; 20( 5): 056025-1-056025-28.[citado 2024 jun. 05 ] Available from: https://doi.org/10.1088/1741-2552/acf734

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