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Filtros : "Oku, Amanda Yumi Ambriola" Limpar

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Artigo de periodico
Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms (2022)
Oku, Amanda Yumi Ambriola ; Barreto, Candida ; Bruneri, Guilherme; Brockington, Guilherme ; Fujita, André ; Sato, João Ricardo
Source: Frontiers in Computational Neuroscience. Unidade: IME
Subjects: TEORIA DOS GRAFOS, NEUROCIÊNCIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OKU, Amanda Yumi Ambriola et al. Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms. Frontiers in Computational Neuroscience, v. 16, 2022Tradução . . Disponível em: https://doi.org/10.3389/fncom.2022.975743. Acesso em: 30 abr. 2024.
APA
Oku, A. Y. A., Barreto, C., Bruneri, G., Brockington, G., Fujita, A., & Sato, J. R. (2022). Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms. Frontiers in Computational Neuroscience, 16. doi:10.3389/fncom.2022.975743
NLM
Oku AYA, Barreto C, Bruneri G, Brockington G, Fujita A, Sato JR. Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms [Internet]. Frontiers in Computational Neuroscience. 2022 ; 16[citado 2024 abr. 30 ] Available from: https://doi.org/10.3389/fncom.2022.975743
Vancouver
Oku AYA, Barreto C, Bruneri G, Brockington G, Fujita A, Sato JR. Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms [Internet]. Frontiers in Computational Neuroscience. 2022 ; 16[citado 2024 abr. 30 ] Available from: https://doi.org/10.3389/fncom.2022.975743
Artigo de periodico
Potential confounders in the analysis of Brazilian adolescent’s health: a combination of machine learning and graph theory (2020)
Oku, Amanda Yumi Ambriola ; Morais, Guilherme Augusto Zimeo ; Bueno, Ana Paula Arantes ; Fujita, André ; Sato, João Ricardo
Source: International Journal of Environmental Research and Public Health. Unidade: IME
Subjects: ADOLESCENTES, TEORIA DOS GRAFOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OKU, Amanda Yumi Ambriola et al. Potential confounders in the analysis of Brazilian adolescent’s health: a combination of machine learning and graph theory. International Journal of Environmental Research and Public Health, v. 17, n. 1, p. 1-10, 2020Tradução . . Disponível em: https://doi.org/10.3390/ijerph17010090. Acesso em: 30 abr. 2024.
APA
Oku, A. Y. A., Morais, G. A. Z., Bueno, A. P. A., Fujita, A., & Sato, J. R. (2020). Potential confounders in the analysis of Brazilian adolescent’s health: a combination of machine learning and graph theory. International Journal of Environmental Research and Public Health, 17( 1), 1-10. doi:10.3390/ijerph17010090
NLM
Oku AYA, Morais GAZ, Bueno APA, Fujita A, Sato JR. Potential confounders in the analysis of Brazilian adolescent’s health: a combination of machine learning and graph theory [Internet]. International Journal of Environmental Research and Public Health. 2020 ; 17( 1): 1-10.[citado 2024 abr. 30 ] Available from: https://doi.org/10.3390/ijerph17010090
Vancouver
Oku AYA, Morais GAZ, Bueno APA, Fujita A, Sato JR. Potential confounders in the analysis of Brazilian adolescent’s health: a combination of machine learning and graph theory [Internet]. International Journal of Environmental Research and Public Health. 2020 ; 17( 1): 1-10.[citado 2024 abr. 30 ] Available from: https://doi.org/10.3390/ijerph17010090

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