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Artigo de periodico
Fast and accurate 3-D spine MRI segmentation using FastCleverSeg (2024)
Ramos, Jonathan da Silva ; Cazzolato, Mirela Teixeira ; Linares, Oscar Alonso Cuadros ; Maciel, Jamilly Gomes; Menezes-Reis, Rafael ; Azevedo-Marques, Paulo Mazzoncini de ; Nogueira-Barbosa, Marcello Henrique ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Magnetic Resonance Imaging. Unidades: FMRP, ICMC
Subjects: RECONHECIMENTO DE IMAGEM, BANCO DE DADOS MULTIMÍDIA, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, RESSONÂNCIA MAGNÉTICA, COLUNA VERTEBRAL
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ABNT
RAMOS, Jonathan da Silva et al. Fast and accurate 3-D spine MRI segmentation using FastCleverSeg. Magnetic Resonance Imaging, v. 109, p. 134-146, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.mri.2024.03.021. Acesso em: 15 out. 2024.
APA
Ramos, J. da S., Cazzolato, M. T., Linares, O. A. C., Maciel, J. G., Menezes-Reis, R., Azevedo-Marques, P. M. de, et al. (2024). Fast and accurate 3-D spine MRI segmentation using FastCleverSeg. Magnetic Resonance Imaging, 109, 134-146. doi:10.1016/j.mri.2024.03.021
NLM
Ramos J da S, Cazzolato MT, Linares OAC, Maciel JG, Menezes-Reis R, Azevedo-Marques PM de, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. Fast and accurate 3-D spine MRI segmentation using FastCleverSeg [Internet]. Magnetic Resonance Imaging. 2024 ; 109 134-146.[citado 2024 out. 15 ] Available from: https://doi.org/10.1016/j.mri.2024.03.021
Vancouver
Ramos J da S, Cazzolato MT, Linares OAC, Maciel JG, Menezes-Reis R, Azevedo-Marques PM de, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. Fast and accurate 3-D spine MRI segmentation using FastCleverSeg [Internet]. Magnetic Resonance Imaging. 2024 ; 109 134-146.[citado 2024 out. 15 ] Available from: https://doi.org/10.1016/j.mri.2024.03.021
Trabalho de evento
KluSIM: speeding up k-medoids clustering over dimensional data with metric access method (2024)
Teixeira, Larissa Roberta ; Eleutério, Igor Alberte Rodrigues ; Cazzolato, Mirela Teixeira ; Gutierrez, Marco Antonio ; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Proceedings. Conference titles: International Conference on Enterprise Information Systems - ICEIS. Unidade: ICMC
Subjects: MINERAÇÃO DE DADOS, RECONHECIMENTO DE PADRÕES, ALGORITMOS ÚTEIS E ESPECÍFICOS
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ABNT
TEIXEIRA, Larissa Roberta et al. KluSIM: speeding up k-medoids clustering over dimensional data with metric access method. 2024, Anais.. Setúbal: SciTePress, 2024. Disponível em: https://doi.org/10.5220/0012599900003690. Acesso em: 15 out. 2024.
APA
Teixeira, L. R., Eleutério, I. A. R., Cazzolato, M. T., Gutierrez, M. A., Traina, A. J. M., & Traina Junior, C. (2024). KluSIM: speeding up k-medoids clustering over dimensional data with metric access method. In Proceedings. Setúbal: SciTePress. doi:10.5220/0012599900003690
NLM
Teixeira LR, Eleutério IAR, Cazzolato MT, Gutierrez MA, Traina AJM, Traina Junior C. KluSIM: speeding up k-medoids clustering over dimensional data with metric access method [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.5220/0012599900003690
Vancouver
Teixeira LR, Eleutério IAR, Cazzolato MT, Gutierrez MA, Traina AJM, Traina Junior C. KluSIM: speeding up k-medoids clustering over dimensional data with metric access method [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.5220/0012599900003690
Trabalho de evento
Similarity-slim extension: reducing financial and computational costs of similarity queries in document collections in NoSQL databases (2024)
Silva, William Zaniboni ; Eleutério, Igor Alberte Rodrigues ; Teixeira, Larissa Roberta ; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Proceedings. Conference titles: International Conference on Enterprise Information Systems - ICEIS. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, BANCO DE DADOS MULTIMÍDIA
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ABNT
SILVA, William Zaniboni et al. Similarity-slim extension: reducing financial and computational costs of similarity queries in document collections in NoSQL databases. 2024, Anais.. Setúbal: SciTePress, 2024. Disponível em: https://doi.org/10.5220/0012606300003690. Acesso em: 15 out. 2024.
APA
Silva, W. Z., Eleutério, I. A. R., Teixeira, L. R., Traina, A. J. M., & Traina Junior, C. (2024). Similarity-slim extension: reducing financial and computational costs of similarity queries in document collections in NoSQL databases. In Proceedings. Setúbal: SciTePress. doi:10.5220/0012606300003690
NLM
Silva WZ, Eleutério IAR, Teixeira LR, Traina AJM, Traina Junior C. Similarity-slim extension: reducing financial and computational costs of similarity queries in document collections in NoSQL databases [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.5220/0012606300003690
Vancouver
Silva WZ, Eleutério IAR, Teixeira LR, Traina AJM, Traina Junior C. Similarity-slim extension: reducing financial and computational costs of similarity queries in document collections in NoSQL databases [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.5220/0012606300003690
Trabalho de evento
MIGUE-Sim: speeding up similarity queries with native RDBMS resources (2024)
Eleutério, Igor Alberte Rodrigues ; Cazzolato, Mirela Teixeira ; Teixeira, Larissa Roberta ; Gutierrez, Marco Antonio ; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Proceedings. Conference titles: ACM/SIGAPP Symposium on Applied Computing - SAC. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, GERENCIADORES DE BANCO DE DADOS
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ABNT
ELEUTÉRIO, Igor Alberte Rodrigues et al. MIGUE-Sim: speeding up similarity queries with native RDBMS resources. 2024, Anais.. New York: ACM, 2024. Disponível em: https://doi.org/10.1145/3605098.3636019. Acesso em: 15 out. 2024.
APA
Eleutério, I. A. R., Cazzolato, M. T., Teixeira, L. R., Gutierrez, M. A., Traina, A. J. M., & Traina Junior, C. (2024). MIGUE-Sim: speeding up similarity queries with native RDBMS resources. In Proceedings. New York: ACM. doi:10.1145/3605098.3636019
NLM
Eleutério IAR, Cazzolato MT, Teixeira LR, Gutierrez MA, Traina AJM, Traina Junior C. MIGUE-Sim: speeding up similarity queries with native RDBMS resources [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1145/3605098.3636019
Vancouver
Eleutério IAR, Cazzolato MT, Teixeira LR, Gutierrez MA, Traina AJM, Traina Junior C. MIGUE-Sim: speeding up similarity queries with native RDBMS resources [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1145/3605098.3636019
Trabalho de evento
A symptom-based community-weighted similarity approach for inpatient health condition monitoring (2024)
Ponciano, Jean Roberto ; Cazzolato, Mirela Teixeira ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: BANCO DE DADOS, RECONHECIMENTO DE PADRÕES, REGISTROS MÉDICOS, TECNOLOGIAS DA SAÚDE
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ABNT
PONCIANO, Jean Roberto et al. A symptom-based community-weighted similarity approach for inpatient health condition monitoring. 2024, Anais.. Los Alamitos: IEEE, 2024. Disponível em: https://doi.org/10.1109/CBMS61543.2024.00050. Acesso em: 15 out. 2024.
APA
Ponciano, J. R., Cazzolato, M. T., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2024). A symptom-based community-weighted similarity approach for inpatient health condition monitoring. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS61543.2024.00050
NLM
Ponciano JR, Cazzolato MT, Gutierrez MA, Traina Junior C, Traina AJM. A symptom-based community-weighted similarity approach for inpatient health condition monitoring [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS61543.2024.00050
Vancouver
Ponciano JR, Cazzolato MT, Gutierrez MA, Traina Junior C, Traina AJM. A symptom-based community-weighted similarity approach for inpatient health condition monitoring [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS61543.2024.00050
Trabalho de evento
RADAR-MIX: how to uncover adversarial attacks in medical image analysis through explainability (2024)
Aguiar, Erikson Júlio de ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: BANCO DE DADOS, VISUALIZAÇÃO, APRENDIZAGEM PROFUNDA, TECNOLOGIAS DA SAÚDE, DIAGNÓSTICO POR IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AGUIAR, Erikson Júlio de e TRAINA JUNIOR, Caetano e TRAINA, Agma Juci Machado. RADAR-MIX: how to uncover adversarial attacks in medical image analysis through explainability. 2024, Anais.. Los Alamitos: IEEE, 2024. Disponível em: https://doi.org/10.1109/CBMS61543.2024.00078. Acesso em: 15 out. 2024.
APA
Aguiar, E. J. de, Traina Junior, C., & Traina, A. J. M. (2024). RADAR-MIX: how to uncover adversarial attacks in medical image analysis through explainability. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS61543.2024.00078
NLM
Aguiar EJ de, Traina Junior C, Traina AJM. RADAR-MIX: how to uncover adversarial attacks in medical image analysis through explainability [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS61543.2024.00078
Vancouver
Aguiar EJ de, Traina Junior C, Traina AJM. RADAR-MIX: how to uncover adversarial attacks in medical image analysis through explainability [Internet]. Proceedings. 2024 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS61543.2024.00078
Artigo de periodico
Security and privacy in machine learning for health systems: strategies and challenges (2023)
Aguiar, Erikson Júlio de ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Yearbook of Medical Informatics. Unidade: ICMC
Subjects: SISTEMAS COMPUTADORIZADOS DE REGISTROS MÉDICOS, APRENDIZADO COMPUTACIONAL, DIAGNÓSTICO POR IMAGEM, DIAGNÓSTICO POR COMPUTADOR, SEGURANÇA DE SOFTWARE, PRIVACIDADE
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ABNT
AGUIAR, Erikson Júlio de e TRAINA JUNIOR, Caetano e TRAINA, Agma Juci Machado. Security and privacy in machine learning for health systems: strategies and challenges. Yearbook of Medical Informatics, v. 32, n. 1, p. 269-281, 2023Tradução . . Disponível em: https://doi.org/10.1055/s-0043-1768731. Acesso em: 15 out. 2024.
APA
Aguiar, E. J. de, Traina Junior, C., & Traina, A. J. M. (2023). Security and privacy in machine learning for health systems: strategies and challenges. Yearbook of Medical Informatics, 32( 1), 269-281. doi:10.1055/s-0043-1768731
NLM
Aguiar EJ de, Traina Junior C, Traina AJM. Security and privacy in machine learning for health systems: strategies and challenges [Internet]. Yearbook of Medical Informatics. 2023 ; 32( 1): 269-281.[citado 2024 out. 15 ] Available from: https://doi.org/10.1055/s-0043-1768731
Vancouver
Aguiar EJ de, Traina Junior C, Traina AJM. Security and privacy in machine learning for health systems: strategies and challenges [Internet]. Yearbook of Medical Informatics. 2023 ; 32( 1): 269-281.[citado 2024 out. 15 ] Available from: https://doi.org/10.1055/s-0043-1768731
Artigo de periodico
Big data em processos de engenharia: desafios e oportunidades (2023)
Traina, Agma Juci Machado ; Cazzolato, Mirela Teixeira ; Gutierrez, Marco Antonio ; Traina Junior, Caetano
Source: Revista ABCM Engenharia. Unidade: ICMC
Subjects: BIG DATA, RECUPERAÇÃO DA INFORMAÇÃO, DESCOBERTA DE CONHECIMENTO, ENGENHARIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TRAINA, Agma Juci Machado et al. Big data em processos de engenharia: desafios e oportunidades. Revista ABCM Engenharia, v. 26, n. 1, p. 34-40, 2023Tradução . . Disponível em: https://www.abcm.org.br/upload/files/ABCM-2023.pdf. Acesso em: 15 out. 2024.
APA
Traina, A. J. M., Cazzolato, M. T., Gutierrez, M. A., & Traina Junior, C. (2023). Big data em processos de engenharia: desafios e oportunidades. Revista ABCM Engenharia, 26( 1), 34-40. Recuperado de https://www.abcm.org.br/upload/files/ABCM-2023.pdf
NLM
Traina AJM, Cazzolato MT, Gutierrez MA, Traina Junior C. Big data em processos de engenharia: desafios e oportunidades [Internet]. Revista ABCM Engenharia. 2023 ; 26( 1): 34-40.[citado 2024 out. 15 ] Available from: https://www.abcm.org.br/upload/files/ABCM-2023.pdf
Vancouver
Traina AJM, Cazzolato MT, Gutierrez MA, Traina Junior C. Big data em processos de engenharia: desafios e oportunidades [Internet]. Revista ABCM Engenharia. 2023 ; 26( 1): 34-40.[citado 2024 out. 15 ] Available from: https://www.abcm.org.br/upload/files/ABCM-2023.pdf
Artigo de periodico
ClinicalPath: a visualization tool to improve the evaluation of electronic health records in clinical decision-making (2023)
Linhares, Claudio Douglas Gouveia ; Lima, Daniel Mário de ; Ponciano, Jean Roberto ; Olivatto, Mauro Marcel ; Gutierrez, Marco Antonio ; Poco, Jorge ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC
Subjects: VISUALIZAÇÃO, INTERAÇÃO USUÁRIO-COMPUTADOR, TECNOLOGIAS DA SAÚDE
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ABNT
LINHARES, Claudio Douglas Gouveia et al. ClinicalPath: a visualization tool to improve the evaluation of electronic health records in clinical decision-making. IEEE Transactions on Visualization and Computer Graphics, v. 29, n. 10, p. 4031-4046, 2023Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2022.3175626. Acesso em: 15 out. 2024.
APA
Linhares, C. D. G., Lima, D. M. de, Ponciano, J. R., Olivatto, M. M., Gutierrez, M. A., Poco, J., et al. (2023). ClinicalPath: a visualization tool to improve the evaluation of electronic health records in clinical decision-making. IEEE Transactions on Visualization and Computer Graphics, 29( 10), 4031-4046. doi:10.1109/TVCG.2022.3175626
NLM
Linhares CDG, Lima DM de, Ponciano JR, Olivatto MM, Gutierrez MA, Poco J, Traina Junior C, Traina AJM. ClinicalPath: a visualization tool to improve the evaluation of electronic health records in clinical decision-making [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( 10): 4031-4046.[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/TVCG.2022.3175626
Vancouver
Linhares CDG, Lima DM de, Ponciano JR, Olivatto MM, Gutierrez MA, Poco J, Traina Junior C, Traina AJM. ClinicalPath: a visualization tool to improve the evaluation of electronic health records in clinical decision-making [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2023 ; 29( 10): 4031-4046.[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/TVCG.2022.3175626
Trabalho de evento
Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings (2023)
Aguiar, Erikson Júlio de ; Costa, Márcus Vinícius Lobo ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AGUIAR, Erikson Júlio de et al. Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00184. Acesso em: 15 out. 2024.
APA
Aguiar, E. J. de, Costa, M. V. L., Traina Junior, C., & Traina, A. J. M. (2023). Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00184
NLM
Aguiar EJ de, Costa MVL, Traina Junior C, Traina AJM. Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings [Internet]. Proceedings. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00184
Vancouver
Aguiar EJ de, Costa MVL, Traina Junior C, Traina AJM. Assessing vulnerabilities of deep learning explainability in medical image analysis under adversarial settings [Internet]. Proceedings. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00184
Trabalho de evento
Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools (2023)
Cazzolato, Mirela Teixeira ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Faloutsos, Christos ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO, VISUALIZAÇÃO, REGISTROS HOSPITALARES
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ABNT
CAZZOLATO, Mirela Teixeira et al. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00202. Acesso em: 15 out. 2024.
APA
Cazzolato, M. T., Gutierrez, M. A., Traina Junior, C., Faloutsos, C., & Traina, A. J. M. (2023). Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00202
NLM
Cazzolato MT, Gutierrez MA, Traina Junior C, Faloutsos C, Traina AJM. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools [Internet]. Proceedings. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
Vancouver
Cazzolato MT, Gutierrez MA, Traina Junior C, Faloutsos C, Traina AJM. Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools [Internet]. Proceedings. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
Trabalho de evento
Similarity grouping by influence: exploring result diversification in similarity group-by operator (2023)
Oliveira, Willian Dener de ; Lauton, Anna Júlia Costa; Traina Junior, Caetano ; Santos, Lúcio Fernandes Dutra
Source: Anais. Conference titles: Simpósio Brasileiro de Bancos de Dados - SBBD. Unidade: ICMC
Subjects: GERENCIADORES DE BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO
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ABNT
OLIVEIRA, Willian Dener de et al. Similarity grouping by influence: exploring result diversification in similarity group-by operator. 2023, Anais.. Porto Alegre: SBC, 2023. Disponível em: https://doi.org/10.5753/sbbd.2023.233430. Acesso em: 15 out. 2024.
APA
Oliveira, W. D. de, Lauton, A. J. C., Traina Junior, C., & Santos, L. F. D. (2023). Similarity grouping by influence: exploring result diversification in similarity group-by operator. In Anais. Porto Alegre: SBC. doi:10.5753/sbbd.2023.233430
NLM
Oliveira WD de, Lauton AJC, Traina Junior C, Santos LFD. Similarity grouping by influence: exploring result diversification in similarity group-by operator [Internet]. Anais. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.5753/sbbd.2023.233430
Vancouver
Oliveira WD de, Lauton AJC, Traina Junior C, Santos LFD. Similarity grouping by influence: exploring result diversification in similarity group-by operator [Internet]. Anais. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.5753/sbbd.2023.233430
Trabalho de evento
A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model (2023)
Costa, Márcus Vinícius Lobo ; Aguiar, Erikson Júlio de ; Rodrigues, Lucas Santiago ; Ramos, Jonathan da Silva ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COSTA, Márcus Vinícius Lobo et al. A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00272. Acesso em: 15 out. 2024.
APA
Costa, M. V. L., Aguiar, E. J. de, Rodrigues, L. S., Ramos, J. da S., Traina Junior, C., & Traina, A. J. M. (2023). A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00272
NLM
Costa MVL, Aguiar EJ de, Rodrigues LS, Ramos J da S, Traina Junior C, Traina AJM. A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model [Internet]. Proceedings. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00272
Vancouver
Costa MVL, Aguiar EJ de, Rodrigues LS, Ramos J da S, Traina Junior C, Traina AJM. A deep learning-based radiomics approach for COVID-19 detection from CXR images using ensemble learning model [Internet]. Proceedings. 2023 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00272
Trabalho de evento
Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures (2022)
Bêdo, Marcos Vinícius Naves; Ramos, Jonathan da Silva ; Traina, Agma Juci Machado ; Traina Junior, Caetano ; Nogueira-Barbosa, Marcello Henrique ; Azevedo-Marques, Paulo Mazzoncini de
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidades: ICMC, FMRP
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, DIAGNÓSTICO POR IMAGEM, RESSONÂNCIA MAGNÉTICA, OSTEOGÊNESE IMPERFEITA, OSTEOPOROSE
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ABNT
BÊDO, Marcos Vinícius Naves et al. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures. 2022, Anais.. Los Alamitos: IEEE, 2022. Disponível em: https://doi.org/10.1109/CBMS55023.2022.00020. Acesso em: 15 out. 2024.
APA
Bêdo, M. V. N., Ramos, J. da S., Traina, A. J. M., Traina Junior, C., Nogueira-Barbosa, M. H., & Azevedo-Marques, P. M. de. (2022). Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS55023.2022.00020
NLM
Bêdo MVN, Ramos J da S, Traina AJM, Traina Junior C, Nogueira-Barbosa MH, Azevedo-Marques PM de. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures [Internet]. Proceedings. 2022 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00020
Vancouver
Bêdo MVN, Ramos J da S, Traina AJM, Traina Junior C, Nogueira-Barbosa MH, Azevedo-Marques PM de. Wia-Spine: a CBIR environment with embedded radiomic features to assess fragility fractures [Internet]. Proceedings. 2022 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00020
Trabalho de evento
Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning (2022)
Ramos, Jonathan da Silva ; Aguiar, Erikson Júlio de ; Belizario, Ivar Vargas ; Costa, Márcus Vinícius Lobo ; Maciel, Jamilly Gomes; Cazzolato, Mirela Teixeira ; Traina Junior, Caetano ; Nogueira-Barbosa, Marcello Henrique ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidades: ICMC, FMRP
Subjects: APRENDIZADO COMPUTACIONAL, TECNOLOGIAS DA SAÚDE, RESSONÂNCIA MAGNÉTICA, DIAGNÓSTICO POR IMAGEM, OSTEOGÊNESE IMPERFEITA, COLUNA VERTEBRAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAMOS, Jonathan da Silva et al. Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning. 2022, Anais.. Los Alamitos: IEEE, 2022. Disponível em: https://doi.org/10.1109/CBMS55023.2022.00021. Acesso em: 15 out. 2024.
APA
Ramos, J. da S., Aguiar, E. J. de, Belizario, I. V., Costa, M. V. L., Maciel, J. G., Cazzolato, M. T., et al. (2022). Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS55023.2022.00021
NLM
Ramos J da S, Aguiar EJ de, Belizario IV, Costa MVL, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning [Internet]. Proceedings. 2022 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00021
Vancouver
Ramos J da S, Aguiar EJ de, Belizario IV, Costa MVL, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. Analysis of vertebrae without fracture on spine MRI to assess bone fragility: a comparison of traditional machine learning and deep learning [Internet]. Proceedings. 2022 ;[citado 2024 out. 15 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00021
Trabalho de evento-anais periodico
Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases (2022)
Aguiar, Erikson Júlio de ; Marcomini, Karem Daiane ; Quirino, Felipe Antunes; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings of SPIE. Conference titles: SPIE Medical Imaging. Unidades: EP, ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, RADIOGRAFIA, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
AGUIAR, Erikson Júlio de et al. Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. Disponível em: https://doi.org/10.1117/12.2611199. Acesso em: 15 out. 2024. , 2022
APA
Aguiar, E. J. de, Marcomini, K. D., Quirino, F. A., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2022). Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases. Proceedings of SPIE. Bellingham: International Society for Optical Engineering - SPIE. doi:10.1117/12.2611199
NLM
Aguiar EJ de, Marcomini KD, Quirino FA, Gutierrez MA, Traina Junior C, Traina AJM. Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases [Internet]. Proceedings of SPIE. 2022 ; 12033 120332P-1-120332P-7.[citado 2024 out. 15 ] Available from: https://doi.org/10.1117/12.2611199
Vancouver
Aguiar EJ de, Marcomini KD, Quirino FA, Gutierrez MA, Traina Junior C, Traina AJM. Evaluation of the impact of physical adversarial attacks on deep learning models for classifying covid cases [Internet]. Proceedings of SPIE. 2022 ; 12033 120332P-1-120332P-7.[citado 2024 out. 15 ] Available from: https://doi.org/10.1117/12.2611199
Trabalho de evento-anais periodico
MiDaS: extract golden results from knowledge discovery even over incomplete databases (2022)
Rodrigues, Lucas Santiago ; Vespa, Thiago Galbiatti ; Eleutério, Igor Alberte Rodrigues; Oliveira, Willian Dener de ; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Lecture Notes in Computer Science. Conference titles: International Conference on Computational Science - ICCS. Unidade: ICMC
Subjects: DESCOBERTA DE CONHECIMENTO, GERENCIADORES DE BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RODRIGUES, Lucas Santiago et al. MiDaS: extract golden results from knowledge discovery even over incomplete databases. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-08760-8_54. Acesso em: 15 out. 2024. , 2022
APA
Rodrigues, L. S., Vespa, T. G., Eleutério, I. A. R., Oliveira, W. D. de, Traina, A. J. M., & Traina Junior, C. (2022). MiDaS: extract golden results from knowledge discovery even over incomplete databases. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-031-08760-8_54
NLM
Rodrigues LS, Vespa TG, Eleutério IAR, Oliveira WD de, Traina AJM, Traina Junior C. MiDaS: extract golden results from knowledge discovery even over incomplete databases [Internet]. Lecture Notes in Computer Science. 2022 ; 13353 653-667.[citado 2024 out. 15 ] Available from: https://doi.org/10.1007/978-3-031-08760-8_54
Vancouver
Rodrigues LS, Vespa TG, Eleutério IAR, Oliveira WD de, Traina AJM, Traina Junior C. MiDaS: extract golden results from knowledge discovery even over incomplete databases [Internet]. Lecture Notes in Computer Science. 2022 ; 13353 653-667.[citado 2024 out. 15 ] Available from: https://doi.org/10.1007/978-3-031-08760-8_54
Artigo de periodico
FeatSet+: visual features extracted from public image datasets (2022)
Cazzolato, Mirela Teixeira ; Scabora, Lucas de Carvalho ; Zabot, Guilherme Felipe ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Journal of Information and Data Management - JIDM. Unidades: EP, ICMC
Subjects: BANCO DE DADOS MULTIMÍDIA, APRENDIZADO COMPUTACIONAL, RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. FeatSet+: visual features extracted from public image datasets. Journal of Information and Data Management - JIDM, v. 13, n. 1, p. 33-48, 2022Tradução . . Disponível em: https://doi.org/10.5753/jidm.2022.2328. Acesso em: 15 out. 2024.
APA
Cazzolato, M. T., Scabora, L. de C., Zabot, G. F., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2022). FeatSet+: visual features extracted from public image datasets. Journal of Information and Data Management - JIDM, 13( 1), 33-48. doi:10.5753/jidm.2022.2328
NLM
Cazzolato MT, Scabora L de C, Zabot GF, Gutierrez MA, Traina Junior C, Traina AJM. FeatSet+: visual features extracted from public image datasets [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 1): 33-48.[citado 2024 out. 15 ] Available from: https://doi.org/10.5753/jidm.2022.2328
Vancouver
Cazzolato MT, Scabora L de C, Zabot GF, Gutierrez MA, Traina Junior C, Traina AJM. FeatSet+: visual features extracted from public image datasets [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 1): 33-48.[citado 2024 out. 15 ] Available from: https://doi.org/10.5753/jidm.2022.2328
Artigo de periodico
Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases (2022)
Cazzolato, Mirela Teixeira ; Rodrigues, Lucas Santiago ; Ribeiro, Marcela Xavier ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Journal of Information and Data Management - JIDM. Unidades: EP, ICMC
Subjects: BANCO DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO, VISUALIZAÇÃO, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases. Journal of Information and Data Management - JIDM, v. 13, n. 2, p. Se 2022, 2022Tradução . . Disponível em: https://doi.org/10.5753/jidm.2022.2484. Acesso em: 15 out. 2024.
APA
Cazzolato, M. T., Rodrigues, L. S., Ribeiro, M. X., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2022). Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases. Journal of Information and Data Management - JIDM, 13( 2), Se 2022. doi:10.5753/jidm.2022.2484
NLM
Cazzolato MT, Rodrigues LS, Ribeiro MX, Gutierrez MA, Traina Junior C, Traina AJM. Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 2): Se 2022.[citado 2024 out. 15 ] Available from: https://doi.org/10.5753/jidm.2022.2484
Vancouver
Cazzolato MT, Rodrigues LS, Ribeiro MX, Gutierrez MA, Traina Junior C, Traina AJM. Sketch+ for visual and correlation-based exploratory data analysis: a case study with COVID-19 databases [Internet]. Journal of Information and Data Management - JIDM. 2022 ; 13( 2): Se 2022.[citado 2024 out. 15 ] Available from: https://doi.org/10.5753/jidm.2022.2484
Artigo de periodico-carta/editorial
Importance of the algorithm as a tool for expert decision making [Editorial]: artificial intelligence in ophthalmology (2022)
Louzada, Ricardo Noguera; Belizario, Ivar Vargas ; Traina, Agma Juci Machado ; Alves, Milton Ruiz
Source: eOftalmo. Unidades: ICMC, FM
Subjects: INTELIGÊNCIA ARTIFICIAL, ALGORITMOS ÚTEIS E ESPECÍFICOS, TECNOLOGIAS DA SAÚDE, OFTALMOLOGIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LOUZADA, Ricardo Noguera et al. Importance of the algorithm as a tool for expert decision making [Editorial]: artificial intelligence in ophthalmology. eOftalmo. São Paulo: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.17545/eOftalmo/2022.0013. Acesso em: 15 out. 2024. , 2022
APA
Louzada, R. N., Belizario, I. V., Traina, A. J. M., & Alves, M. R. (2022). Importance of the algorithm as a tool for expert decision making [Editorial]: artificial intelligence in ophthalmology. eOftalmo. São Paulo: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.17545/eOftalmo/2022.0013
NLM
Louzada RN, Belizario IV, Traina AJM, Alves MR. Importance of the algorithm as a tool for expert decision making [Editorial]: artificial intelligence in ophthalmology [Internet]. eOftalmo. 2022 ; 8( 3): 61-64.[citado 2024 out. 15 ] Available from: https://doi.org/10.17545/eOftalmo/2022.0013
Vancouver
Louzada RN, Belizario IV, Traina AJM, Alves MR. Importance of the algorithm as a tool for expert decision making [Editorial]: artificial intelligence in ophthalmology [Internet]. eOftalmo. 2022 ; 8( 3): 61-64.[citado 2024 out. 15 ] Available from: https://doi.org/10.17545/eOftalmo/2022.0013

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