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Artigo de periodico
Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models (2023)
Soares, Andrey Coatrini ; Soares, Juliana Coatrini ; Popolin Neto, Mário ; Mello, Suelen Scarpa de; Pinto, Danielle Dos Santos Cinelli; Carvalho, Wanessa Araújo; Gilmore, Michael Shaffer; Piazzetta, Maria Helena de Oliveira; Gobbi, Angelo Luiz ; Brandão, Humberto de Mello; Paulovich, Fernando Vieira ; Oliveira Junior, Osvaldo Novais de ; Mattoso, Luiz Henrique Capparelli
Source: Chemical Engineering Journal. Unidades: IFSC, ICMC
Subjects: MASTITE ANIMAL, ELETROQUÍMICA, APRENDIZADO COMPUTACIONAL, PECUÁRIA LEITEIRA, MONITORAMENTO AMBIENTAL, STAPHYLOCOCCUS, SENSOR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOARES, Andrey Coatrini et al. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. Chemical Engineering Journal, v. 451, n. Ja 2023, p. 138523-1-138523-9, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.cej.2022.138523. Acesso em: 14 jul. 2024.
APA
Soares, A. C., Soares, J. C., Popolin Neto, M., Mello, S. S. de, Pinto, D. D. S. C., Carvalho, W. A., et al. (2023). Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. Chemical Engineering Journal, 451( Ja 2023), 138523-1-138523-9. doi:10.1016/j.cej.2022.138523
NLM
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Pinto DDSC, Carvalho WA, Gilmore MS, Piazzetta MH de O, Gobbi AL, Brandão H de M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models [Internet]. Chemical Engineering Journal. 2023 ; 451( Ja 2023): 138523-1-138523-9.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.cej.2022.138523
Vancouver
Soares AC, Soares JC, Popolin Neto M, Mello SS de, Pinto DDSC, Carvalho WA, Gilmore MS, Piazzetta MH de O, Gobbi AL, Brandão H de M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models [Internet]. Chemical Engineering Journal. 2023 ; 451( Ja 2023): 138523-1-138523-9.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.cej.2022.138523
Artigo de periodico
Detection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space (2022)
Soares, Juliana Coatrini ; Soares, Andrey Coatrini ; Popolin Neto, Mário ; Paulovich, Fernando Vieira ; Oliveira Junior, Osvaldo Novais de ; Mattoso, Luiz Henrique Capparelli
Source: Sensors and Actuators Reports. Unidades: ICMC, IFSC
Subjects: APRENDIZADO COMPUTACIONAL, ESPECTROSCOPIA, MASTITE ANIMAL, PECUÁRIA LEITEIRA, STAPHYLOCOCCUS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOARES, Juliana Coatrini et al. Detection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space. Sensors and Actuators Reports, v. No 2022, p. 100083-1-100083-10, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.snr.2022.100083. Acesso em: 14 jul. 2024.
APA
Soares, J. C., Soares, A. C., Popolin Neto, M., Paulovich, F. V., Oliveira Junior, O. N. de, & Mattoso, L. H. C. (2022). Detection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space. Sensors and Actuators Reports, No 2022, 100083-1-100083-10. doi:10.1016/j.snr.2022.100083
NLM
Soares JC, Soares AC, Popolin Neto M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Detection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space [Internet]. Sensors and Actuators Reports. 2022 ; No 2022 100083-1-100083-10.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.snr.2022.100083
Vancouver
Soares JC, Soares AC, Popolin Neto M, Paulovich FV, Oliveira Junior ON de, Mattoso LHC. Detection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space [Internet]. Sensors and Actuators Reports. 2022 ; No 2022 100083-1-100083-10.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1016/j.snr.2022.100083
Artigo de periodico
Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques (2021)
Soares, Juliana Coatrini ; Soares, Andrey Coatrini ; Rodrigues, Valquiria da Cruz; Oiticica, Pedro Ramon Almeida ; Raymundo-Pereira, Paulo Augusto ; Bott Neto, José Luiz ; Buscaglia, Lorenzo A ; Castro, Lucas Daniel Chiba de ; Ribas, Lucas Correia ; Scabini, Leonardo Felipe dos Santos ; Brazaca, Lais Canniatti ; Correa, Daniel S. ; Mattoso, Luiz Henrique C; Oliveira, Maria Cristina Ferreira de ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Carrilho, Emanuel ; Bruno, Odemir Martinez ; Melendez, Matias Eliseo ; Oliveira Junior, Osvaldo Novais de
Source: Materials Chemistry Frontiers. Unidades: ICMC, IQSC, IFSC
Subjects: CORONAVIRUS, COVID-19, DIAGNÓSTICO, SENSOR, SEQUÊNCIA DO DNA, VISUALIZAÇÃO, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOARES, Juliana Coatrini et al. Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques. Materials Chemistry Frontiers, v. 5, n. 15, p. 5658-5670, 2021Tradução . . Disponível em: https://doi.org/10.1039/D1QM00665G. Acesso em: 14 jul. 2024.
APA
Soares, J. C., Soares, A. C., Rodrigues, V. da C., Oiticica, P. R. A., Raymundo-Pereira, P. A., Bott Neto, J. L., et al. (2021). Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques. Materials Chemistry Frontiers, 5( 15), 5658-5670. doi:10.1039/D1QM00665G
NLM
Soares JC, Soares AC, Rodrigues V da C, Oiticica PRA, Raymundo-Pereira PA, Bott Neto JL, Buscaglia LA, Castro LDC de, Ribas LC, Scabini LF dos S, Brazaca LC, Correa DS, Mattoso LHC, Oliveira MCF de, Carvalho ACP de LF de, Carrilho E, Bruno OM, Melendez ME, Oliveira Junior ON de. Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques [Internet]. Materials Chemistry Frontiers. 2021 ; 5( 15): 5658-5670.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1039/D1QM00665G
Vancouver
Soares JC, Soares AC, Rodrigues V da C, Oiticica PRA, Raymundo-Pereira PA, Bott Neto JL, Buscaglia LA, Castro LDC de, Ribas LC, Scabini LF dos S, Brazaca LC, Correa DS, Mattoso LHC, Oliveira MCF de, Carvalho ACP de LF de, Carrilho E, Bruno OM, Melendez ME, Oliveira Junior ON de. Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques [Internet]. Materials Chemistry Frontiers. 2021 ; 5( 15): 5658-5670.[citado 2024 jul. 14 ] Available from: https://doi.org/10.1039/D1QM00665G

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