Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques (2017)
- Authors:
- Autor USP: ROSA, JOÃO LUIS GARCIA - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-319-69775-8_7
- Subjects: APRENDIZADO COMPUTACIONAL; MINERAÇÃO DE DADOS; RECONHECIMENTO DE PADRÕES; ELETROENCEFALOGRAFIA; EPILEPSIA
- Keywords: EEG; Cross-correlation; Predictive models; Classification
- Language: Inglês
- Imprenta:
- Source:
- Título: Lecture Notes in Artificial Intelligence
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 10344, p. 134-145, 2017
- Conference titles: Banff International Research Station for Mathematical Innovation and Discovery Workshop - BIRS
- Status:
- Nenhuma versão em acesso aberto identificada
-
ABNT
OLIVA, Jefferson Tales e ROSA, João Luís Garcia. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-69775-8_7. Acesso em: 26 mar. 2026. , 2017 -
APA
Oliva, J. T., & Rosa, J. L. G. (2017). Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-319-69775-8_7 -
NLM
Oliva JT, Rosa JLG. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10344 134-145.[citado 2026 mar. 26 ] Available from: https://doi.org/10.1007/978-3-319-69775-8_7 -
Vancouver
Oliva JT, Rosa JLG. Predictive models for differentiation between normal and abnormal EEG through cross-correlation and machine learning techniques [Internet]. Lecture Notes in Artificial Intelligence. 2017 ; 10344 134-145.[citado 2026 mar. 26 ] Available from: https://doi.org/10.1007/978-3-319-69775-8_7 - Artificial neural networks: models and applications
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