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Trabalho de evento
Improving medication identification accuracy and regulatory compliance through NLP and ontologies: an analysis of otorhinolaryngology prescriptions (2024)
Miranda, Nelson Julio de Oliveira ; Ferreira, Allan; Peres, Reinaldo Porte ; Botega, Leonardo Castro ; Moreira, Dilvan de Abreu
Source: Proceedings. Conference titles: International Conference on Enabling Technologies : Infrastructure for Collaborative Enterprises - WETICE. Unidade: ICMC
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, ONTOLOGIAS, MEDICAMENTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MIRANDA, Nelson Julio de Oliveira et al. Improving medication identification accuracy and regulatory compliance through NLP and ontologies: an analysis of otorhinolaryngology prescriptions. 2024, Anais.. Los Alamitos: IEEE, 2024. Disponível em: https://doi.org/10.1109/WETICE64632.2024.00032. Acesso em: 08 nov. 2025.
APA
Miranda, N. J. de O., Ferreira, A., Peres, R. P., Botega, L. C., & Moreira, D. de A. (2024). Improving medication identification accuracy and regulatory compliance through NLP and ontologies: an analysis of otorhinolaryngology prescriptions. In Proceedings. Los Alamitos: IEEE. doi:10.1109/WETICE64632.2024.00032
NLM
Miranda NJ de O, Ferreira A, Peres RP, Botega LC, Moreira D de A. Improving medication identification accuracy and regulatory compliance through NLP and ontologies: an analysis of otorhinolaryngology prescriptions [Internet]. Proceedings. 2024 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/WETICE64632.2024.00032
Vancouver
Miranda NJ de O, Ferreira A, Peres RP, Botega LC, Moreira D de A. Improving medication identification accuracy and regulatory compliance through NLP and ontologies: an analysis of otorhinolaryngology prescriptions [Internet]. Proceedings. 2024 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/WETICE64632.2024.00032
Trabalho de evento
Feature selection using complex networks to support price trend forecast in energy markets (2023)
Castilho, Douglas; Santos, Moises Rocha dos ; Tinós, Renato ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Paula, Marcos Basile Saviano de; Ladeira, Lucas; Guarnier, Ewerton ; Silva Filho, Donato ; Suiama, Danilo Y; Macedo Junior, Edmur A; Alipio, Lucas P
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: FFCLRP, ICMC
Subjects: REDES COMPLEXAS, APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), ENERGIA ELÉTRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASTILHO, Douglas et al. Feature selection using complex networks to support price trend forecast in energy markets. 2023, Anais.. Piscataway: IEEE, 2023. Disponível em: https://doi.org/10.1109/IJCNN54540.2023.10191426. Acesso em: 08 nov. 2025.
APA
Castilho, D., Santos, M. R. dos, Tinós, R., Carvalho, A. C. P. de L. F. de, Paula, M. B. S. de, Ladeira, L., et al. (2023). Feature selection using complex networks to support price trend forecast in energy markets. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN54540.2023.10191426
NLM
Castilho D, Santos MR dos, Tinós R, Carvalho ACP de LF de, Paula MBS de, Ladeira L, Guarnier E, Silva Filho D, Suiama DY, Macedo Junior EA, Alipio LP. Feature selection using complex networks to support price trend forecast in energy markets [Internet]. Proceedings. 2023 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191426
Vancouver
Castilho D, Santos MR dos, Tinós R, Carvalho ACP de LF de, Paula MBS de, Ladeira L, Guarnier E, Silva Filho D, Suiama DY, Macedo Junior EA, Alipio LP. Feature selection using complex networks to support price trend forecast in energy markets [Internet]. Proceedings. 2023 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/IJCNN54540.2023.10191426
Trabalho de evento
Machine learning approach for trend prediction to improve returns on brazilian energy market (2022)
Santos, Moises Rocha dos ; Braz, Douglas Donizeti de Castilho; Carvalho, André Carlos Ponce de Leon Ferreira de ; Tinós, Renato ; Paula, Marcos Basile Saviano de; Doretto, Gabriel; Guarnier, Ewerton ; Silva Filho, Donato ; Suiama, Danilo Y; Ferreira, Lorena E; Carmo Junior, José E
Source: Proceedings. Conference titles: IEEE Latin American Conference on Computational Intelligence - LA-CCI. Unidades: ICMC, FFCLRP
Subjects: APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), ENERGIA ELÉTRICA, POLÍTICA DE PREÇO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Moises Rocha dos et al. Machine learning approach for trend prediction to improve returns on brazilian energy market. 2022, Anais.. Los Alamitos: IEEE, 2022. Disponível em: https://doi.org/10.1109/LA-CCI54402.2022.9981846. Acesso em: 08 nov. 2025.
APA
Santos, M. R. dos, Braz, D. D. de C., Carvalho, A. C. P. de L. F. de, Tinós, R., Paula, M. B. S. de, Doretto, G., et al. (2022). Machine learning approach for trend prediction to improve returns on brazilian energy market. In Proceedings. Los Alamitos: IEEE. doi:10.1109/LA-CCI54402.2022.9981846
NLM
Santos MR dos, Braz DD de C, Carvalho ACP de LF de, Tinós R, Paula MBS de, Doretto G, Guarnier E, Silva Filho D, Suiama DY, Ferreira LE, Carmo Junior JE. Machine learning approach for trend prediction to improve returns on brazilian energy market [Internet]. Proceedings. 2022 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/LA-CCI54402.2022.9981846
Vancouver
Santos MR dos, Braz DD de C, Carvalho ACP de LF de, Tinós R, Paula MBS de, Doretto G, Guarnier E, Silva Filho D, Suiama DY, Ferreira LE, Carmo Junior JE. Machine learning approach for trend prediction to improve returns on brazilian energy market [Internet]. Proceedings. 2022 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/LA-CCI54402.2022.9981846
Trabalho de evento
Seasonal-trend decomposition based on Loess + machine learning: hybrid forecasting for monthly univariate time series (2021)
Silvestre, Gabriel Dalforno; Santos, Moises Rocha dos ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVESTRE, Gabriel Dalforno e SANTOS, Moises Rocha dos e CARVALHO, André Carlos Ponce de Leon Ferreira de. Seasonal-trend decomposition based on Loess + machine learning: hybrid forecasting for monthly univariate time series. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/IJCNN52387.2021.9533644. Acesso em: 08 nov. 2025.
APA
Silvestre, G. D., Santos, M. R. dos, & Carvalho, A. C. P. de L. F. de. (2021). Seasonal-trend decomposition based on Loess + machine learning: hybrid forecasting for monthly univariate time series. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN52387.2021.9533644
NLM
Silvestre GD, Santos MR dos, Carvalho ACP de LF de. Seasonal-trend decomposition based on Loess + machine learning: hybrid forecasting for monthly univariate time series [Internet]. Proceedings. 2021 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/IJCNN52387.2021.9533644
Vancouver
Silvestre GD, Santos MR dos, Carvalho ACP de LF de. Seasonal-trend decomposition based on Loess + machine learning: hybrid forecasting for monthly univariate time series [Internet]. Proceedings. 2021 ;[citado 2025 nov. 08 ] Available from: https://doi.org/10.1109/IJCNN52387.2021.9533644

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