Anomaly detection through temporal abstractions on intensive care data: position paper (2017)
- Authors:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.1109/CBMS.2017.146
- Subjects: APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE PADRÕES; ANÁLISE DE SÉRIES TEMPORAIS; COMPUTAÇÃO APLICADA
- Keywords: Anomaly detection; outlier detection; temporal abstraction; intensive care
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2017
- Source:
- Título: Proceedings
- ISSN: 2372-9198
- Conference titles: International Symposium on Computer-Based Medical Systems - CBMS
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
GELATTI, Giovana Jaskulski e CARVALHO, André Carlos Ponce de Leon Ferreira de e RODRIGUES, Pedro Pereira. Anomaly detection through temporal abstractions on intensive care data: position paper. 2017, Anais.. Los Alamitos: IEEE, 2017. Disponível em: https://doi.org/10.1109/CBMS.2017.146. Acesso em: 03 fev. 2026. -
APA
Gelatti, G. J., Carvalho, A. C. P. de L. F. de, & Rodrigues, P. P. (2017). Anomaly detection through temporal abstractions on intensive care data: position paper. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2017.146 -
NLM
Gelatti GJ, Carvalho ACP de LF de, Rodrigues PP. Anomaly detection through temporal abstractions on intensive care data: position paper [Internet]. Proceedings. 2017 ;[citado 2026 fev. 03 ] Available from: https://doi.org/10.1109/CBMS.2017.146 -
Vancouver
Gelatti GJ, Carvalho ACP de LF de, Rodrigues PP. Anomaly detection through temporal abstractions on intensive care data: position paper [Internet]. Proceedings. 2017 ;[citado 2026 fev. 03 ] Available from: https://doi.org/10.1109/CBMS.2017.146 - Gabinete pequeno é destaque de pc itautec
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Informações sobre o DOI: 10.1109/CBMS.2017.146 (Fonte: oaDOI API)
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