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Trabalho de evento-resumo periodico
Convnext for the classification of oral potentially malignant disorders and squamous cell carcinoma (2024)
Araujo, Anna Luiza Damaceno ; Souza, Eduardo Santos Carlos de; Saldivia-Siracusa, Cristina ; Lopes, Márcio Ajudarte ; Carvalho, Andre Carlos Ponce de Leon Ferreira de ; Santos-Silva, Alan Roger dos ; Kowalski, Luiz Paulo
Source: Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. Conference titles: Brazilian Congress of Stomatology and Oral Pathology - SOBEP. Unidades: ICMC, FM
Subjects: APRENDIZAGEM PROFUNDA, RECONHECIMENTO DE IMAGEM, NEOPLASIAS BUCAIS, NEOPLASIAS DE CABEÇA E PESCOÇO, TECNOLOGIAS DA SAÚDE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ARAUJO, Anna Luiza Damaceno et al. Convnext for the classification of oral potentially malignant disorders and squamous cell carcinoma. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. New York: Elsevier. Disponível em: https://doi.org/10.1016/j.oooo.2023.12.694. Acesso em: 01 nov. 2024. , 2024
APA
Araujo, A. L. D., Souza, E. S. C. de, Saldivia-Siracusa, C., Lopes, M. A., Carvalho, A. C. P. de L. F. de, Santos-Silva, A. R. dos, & Kowalski, L. P. (2024). Convnext for the classification of oral potentially malignant disorders and squamous cell carcinoma. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. New York: Elsevier. doi:10.1016/j.oooo.2023.12.694
NLM
Araujo ALD, Souza ESC de, Saldivia-Siracusa C, Lopes MA, Carvalho ACP de LF de, Santos-Silva AR dos, Kowalski LP. Convnext for the classification of oral potentially malignant disorders and squamous cell carcinoma [Internet]. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. 2024 ; 137( 6): e296-e297.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.oooo.2023.12.694
Vancouver
Araujo ALD, Souza ESC de, Saldivia-Siracusa C, Lopes MA, Carvalho ACP de LF de, Santos-Silva AR dos, Kowalski LP. Convnext for the classification of oral potentially malignant disorders and squamous cell carcinoma [Internet]. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. 2024 ; 137( 6): e296-e297.[citado 2024 nov. 01 ] Available from: https://doi.org/10.1016/j.oooo.2023.12.694
Artigo de periodico
Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas (2023)
Giraldo-Roldán, Daniela ; Ribeiro, Erin Crespo Cordeiro ; Araujo, Anna Luiza Damaceno ; Penafort, Paulo Victor Mendes ; Silva, Viviane Mariano da ; Câmara, Jeconias ; Pontes, Helder Antônio Rebelo ; Martins, Manoela Domingues ; Oliveira, Márcio Campos ; Santos-Silva, Alan Roger dos ; Lopes, Márcio Ajudarte ; Kowalski, Luiz Paulo ; Moraes, Matheus Cardoso ; Vargas, Pablo Agustin
Source: JOURNAL OF ORAL PATHOLOGY & MEDICINE. Unidade: FM
Subjects: APRENDIZAGEM PROFUNDA, AMELOBLASTO, AMELOBLASTOMA, INTELIGÊNCIA ARTIFICIAL, TUMORES ODONTOGÊNICOS
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ABNT
GIRALDO-ROLDÁN, Daniela et al. Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas. JOURNAL OF ORAL PATHOLOGY & MEDICINE, v. 52, n. 10, p. 988-995, 2023Tradução . . Disponível em: https://observatorio.fm.usp.br/handle/OPI/57802. Acesso em: 01 nov. 2024.
APA
Giraldo-Roldán, D., Ribeiro, E. C. C., Araujo, A. L. D., Penafort, P. V. M., Silva, V. M. da, Câmara, J., et al. (2023). Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas. JOURNAL OF ORAL PATHOLOGY & MEDICINE, 52( 10), 988-995. doi:10.1111/jop.13481
NLM
Giraldo-Roldán D, Ribeiro ECC, Araujo ALD, Penafort PVM, Silva VM da, Câmara J, Pontes HAR, Martins MD, Oliveira MC, Santos-Silva AR dos, Lopes MA, Kowalski LP, Moraes MC, Vargas PA. Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas [Internet]. JOURNAL OF ORAL PATHOLOGY & MEDICINE. 2023 ; 52( 10): 988-995.[citado 2024 nov. 01 ] Available from: https://observatorio.fm.usp.br/handle/OPI/57802
Vancouver
Giraldo-Roldán D, Ribeiro ECC, Araujo ALD, Penafort PVM, Silva VM da, Câmara J, Pontes HAR, Martins MD, Oliveira MC, Santos-Silva AR dos, Lopes MA, Kowalski LP, Moraes MC, Vargas PA. Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas [Internet]. JOURNAL OF ORAL PATHOLOGY & MEDICINE. 2023 ; 52( 10): 988-995.[citado 2024 nov. 01 ] Available from: https://observatorio.fm.usp.br/handle/OPI/57802
Trabalho de evento
Discriminant audio properties in deep learning based respiratory insufficiency detection in brazilian portuguese (2023)
Gauy, Marcelo Matheus ; Berti, Larissa Cristina ; Candido Junior, Arnaldo ; Camargo Neto, Augusto César de; Goldman, Alfredo ; Levin, Anna Sara ; Martins, Marcus Vinícius Moreira ; Medeiros, Beatriz Raposo de ; Queiroz, Marcelo Gomes de ; Sabino, Ester Cerdeira ; Svartman, Flaviane Fernandes ; Finger, Marcelo
Source: Proceedings. Conference titles: International Conference on Artificial Intelligence in Medicine - AIME. Unidades: IME, FM, FFLCH
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZAGEM PROFUNDA, INSUFICIÊNCIA RESPIRATÓRIA, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GAUY, Marcelo Matheus et al. Discriminant audio properties in deep learning based respiratory insufficiency detection in brazilian portuguese. 2023, Anais.. Cham: Springer, 2023. Disponível em: https://doi.org/10.1007/978-3-031-34344-5_32. Acesso em: 01 nov. 2024.
APA
Gauy, M. M., Berti, L. C., Candido Junior, A., Camargo Neto, A. C. de, Goldman, A., Levin, A. S., et al. (2023). Discriminant audio properties in deep learning based respiratory insufficiency detection in brazilian portuguese. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-34344-5_32
NLM
Gauy MM, Berti LC, Candido Junior A, Camargo Neto AC de, Goldman A, Levin AS, Martins MVM, Medeiros BR de, Queiroz MG de, Sabino EC, Svartman FF, Finger M. Discriminant audio properties in deep learning based respiratory insufficiency detection in brazilian portuguese [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/978-3-031-34344-5_32
Vancouver
Gauy MM, Berti LC, Candido Junior A, Camargo Neto AC de, Goldman A, Levin AS, Martins MVM, Medeiros BR de, Queiroz MG de, Sabino EC, Svartman FF, Finger M. Discriminant audio properties in deep learning based respiratory insufficiency detection in brazilian portuguese [Internet]. Proceedings. 2023 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1007/978-3-031-34344-5_32
Trabalho de evento
Deep learning against COVID-19: respiratory insufficiency detection in brazilian portuguese speech (2021)
Casanova, Edresson ; Gris, Lucas; Camargo, Augusto; Silva, Daniel da; Gazzola, Murilo Gleyson ; Sabino, Ester Cerdeira ; Levin, Anna Sara Shafferman ; Candido Junior, Arnaldo ; Aluísio, Sandra Maria ; Finger, Marcelo
Source: Proceedings. Conference titles: Annual Meeting of the Association for Computational Linguistics - ACL. Unidades: FM, ICMC, IME
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, APRENDIZAGEM PROFUNDA, REDES NEURAIS, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, INSUFICIÊNCIA RESPIRATÓRIA, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASANOVA, Edresson et al. Deep learning against COVID-19: respiratory insufficiency detection in brazilian portuguese speech. 2021, Anais.. Stroudsburg: ACL, 2021. Disponível em: https://doi.org/10.18653/v1/2021.findings-acl.55. Acesso em: 01 nov. 2024.
APA
Casanova, E., Gris, L., Camargo, A., Silva, D. da, Gazzola, M. G., Sabino, E. C., et al. (2021). Deep learning against COVID-19: respiratory insufficiency detection in brazilian portuguese speech. In Proceedings. Stroudsburg: ACL. doi:10.18653/v1/2021.findings-acl.55
NLM
Casanova E, Gris L, Camargo A, Silva D da, Gazzola MG, Sabino EC, Levin ASS, Candido Junior A, Aluísio SM, Finger M. Deep learning against COVID-19: respiratory insufficiency detection in brazilian portuguese speech [Internet]. Proceedings. 2021 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.18653/v1/2021.findings-acl.55
Vancouver
Casanova E, Gris L, Camargo A, Silva D da, Gazzola MG, Sabino EC, Levin ASS, Candido Junior A, Aluísio SM, Finger M. Deep learning against COVID-19: respiratory insufficiency detection in brazilian portuguese speech [Internet]. Proceedings. 2021 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.18653/v1/2021.findings-acl.55
Trabalho de evento
Automatic segmentation of posterior fossa structures in pediatric brain MRIs (2021)
Oliveira, Hugo ; Dias, Larissa de Oliveira Penteado ; Pimenta, José Luiz Maciel ; Ferraciolli, Suely Fazio ; Takahashi, Marcelo Straus ; Bloch, Isabelle ; César Júnior, Roberto Marcondes
Source: Proceedings. Conference titles: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidades: IME, FM
Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZAGEM PROFUNDA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Hugo et al. Automatic segmentation of posterior fossa structures in pediatric brain MRIs. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00025. Acesso em: 01 nov. 2024.
APA
Oliveira, H., Dias, L. de O. P., Pimenta, J. L. M., Ferraciolli, S. F., Takahashi, M. S., Bloch, I., & César Júnior, R. M. (2021). Automatic segmentation of posterior fossa structures in pediatric brain MRIs. In Proceedings. Piscataway: IEEE. doi:10.1109/SIBGRAPI54419.2021.00025
NLM
Oliveira H, Dias L de OP, Pimenta JLM, Ferraciolli SF, Takahashi MS, Bloch I, César Júnior RM. Automatic segmentation of posterior fossa structures in pediatric brain MRIs [Internet]. Proceedings. 2021 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00025
Vancouver
Oliveira H, Dias L de OP, Pimenta JLM, Ferraciolli SF, Takahashi MS, Bloch I, César Júnior RM. Automatic segmentation of posterior fossa structures in pediatric brain MRIs [Internet]. Proceedings. 2021 ;[citado 2024 nov. 01 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00025
Trabalho de evento
Detection of architectural distortion with deep convolutional neural network and data augmentation of limited dataset (2019)
Costa, Arthur C; Oliveira, Helder Cesar Rodrigues de; Catani, Juliana H; Barros, Nestor de; Melo, Carlos F. E; Vieira, Marcelo Andrade da Costa
Source: IFMBE Proceedings. Conference titles: Brazilian Congress on Biomedical Engineering. Unidades: EESC, FM
Subjects: MAMOGRAFIA, NEOPLASIAS MAMÁRIAS, APRENDIZAGEM PROFUNDA, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COSTA, Arthur C et al. Detection of architectural distortion with deep convolutional neural network and data augmentation of limited dataset. 2019, Anais.. Singapore: Escola de Engenharia de São Carlos, Universidade de São Paulo, 2019. Disponível em: https://repositorio.usp.br/directbitstream/ae99db0e-9613-4c4e-9857-b41536b8ad14/sysno3190509_capitulo%20de%20livro%2003.pdf. Acesso em: 01 nov. 2024.
APA
Costa, A. C., Oliveira, H. C. R. de, Catani, J. H., Barros, N. de, Melo, C. F. E., & Vieira, M. A. da C. (2019). Detection of architectural distortion with deep convolutional neural network and data augmentation of limited dataset. In IFMBE Proceedings. Singapore: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1007/978-981-13-2517-5_24
NLM
Costa AC, Oliveira HCR de, Catani JH, Barros N de, Melo CFE, Vieira MA da C. Detection of architectural distortion with deep convolutional neural network and data augmentation of limited dataset [Internet]. IFMBE Proceedings. 2019 ;[citado 2024 nov. 01 ] Available from: https://repositorio.usp.br/directbitstream/ae99db0e-9613-4c4e-9857-b41536b8ad14/sysno3190509_capitulo%20de%20livro%2003.pdf
Vancouver
Costa AC, Oliveira HCR de, Catani JH, Barros N de, Melo CFE, Vieira MA da C. Detection of architectural distortion with deep convolutional neural network and data augmentation of limited dataset [Internet]. IFMBE Proceedings. 2019 ;[citado 2024 nov. 01 ] Available from: https://repositorio.usp.br/directbitstream/ae99db0e-9613-4c4e-9857-b41536b8ad14/sysno3190509_capitulo%20de%20livro%2003.pdf

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