Differentiation between normal and epileptic EEG using k-nearest-neighbors technique (2016)
Source: Machine learning for health informatics : state-of-art and the future challenges. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS, ELETROENCEFALOGRAFIA, EPILEPSIA
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OLIVA, Jefferson Tales e ROSA, João Luís Garcia. Differentiation between normal and epileptic EEG using k-nearest-neighbors technique. Machine learning for health informatics : state-of-art and the future challenges. Tradução . Cham: Springer, 2016. . Disponível em: https://doi.org/10.1007/978-3-319-50478-0_7. Acesso em: 28 abr. 2024.APA
Oliva, J. T., & Rosa, J. L. G. (2016). Differentiation between normal and epileptic EEG using k-nearest-neighbors technique. In Machine learning for health informatics : state-of-art and the future challenges. Cham: Springer. doi:10.1007/978-3-319-50478-0_7NLM
Oliva JT, Rosa JLG. Differentiation between normal and epileptic EEG using k-nearest-neighbors technique [Internet]. In: Machine learning for health informatics : state-of-art and the future challenges. Cham: Springer; 2016. [citado 2024 abr. 28 ] Available from: https://doi.org/10.1007/978-3-319-50478-0_7Vancouver
Oliva JT, Rosa JLG. Differentiation between normal and epileptic EEG using k-nearest-neighbors technique [Internet]. In: Machine learning for health informatics : state-of-art and the future challenges. Cham: Springer; 2016. [citado 2024 abr. 28 ] Available from: https://doi.org/10.1007/978-3-319-50478-0_7
