Source: Biology Methods and Protocols. Unidade: ICMC
Subjects: COVID-19, REDES COMPLEXAS, APRENDIZAGEM PROFUNDA, AVALIAÇÃO DE AÇÕES DE SAÚDE PÚBLICA
ABNT
ALVES, Caroline Lourenço et al. Harnessing multi-output machine learning approach and dynamical observables from network structure to optimize COVID-19 intervention strategies. Biology Methods and Protocols, v. 10, n. 1, p. 1-11, 2025Tradução . . Disponível em: https://doi.org/10.1093/biomethods/bpaf039. Acesso em: 01 dez. 2025.APA
Alves, C. L., Kuhnert, K., Rodrigues, F. A., & Moeckel, M. (2025). Harnessing multi-output machine learning approach and dynamical observables from network structure to optimize COVID-19 intervention strategies. Biology Methods and Protocols, 10( 1), 1-11. doi:10.1093/biomethods/bpaf039NLM
Alves CL, Kuhnert K, Rodrigues FA, Moeckel M. Harnessing multi-output machine learning approach and dynamical observables from network structure to optimize COVID-19 intervention strategies [Internet]. Biology Methods and Protocols. 2025 ; 10( 1): 1-11.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1093/biomethods/bpaf039Vancouver
Alves CL, Kuhnert K, Rodrigues FA, Moeckel M. Harnessing multi-output machine learning approach and dynamical observables from network structure to optimize COVID-19 intervention strategies [Internet]. Biology Methods and Protocols. 2025 ; 10( 1): 1-11.[citado 2025 dez. 01 ] Available from: https://doi.org/10.1093/biomethods/bpaf039

