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Trabalho de evento
Modeling clinical data with attention: a knowledge graph approach with CliniKG (2025)
Moura, Eduardo; Conrado, Rafael Comitre Garcia ; Campos, Leonardo de Oliveira; Olivatto, Mauro Marcel ; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado ; Cazzolato, Mirela Teixeira
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FM, ICMC, FFCLRP
Subjects: MINERAÇÃO DE DADOS, PROCESSAMENTO DE LINGUAGEM NATURAL, TEORIA DOS GRAFOS, SISTEMAS COMPUTADORIZADOS DE REGISTROS MÉDICOS, VISUALIZAÇÃO
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ABNT
MOURA, Eduardo et al. Modeling clinical data with attention: a knowledge graph approach with CliniKG. 2025, Anais.. Los Alamitos: IEEE, 2025. Disponível em: https://doi.org/10.1109/CBMS65348.2025.00156. Acesso em: 29 nov. 2025.
APA
Moura, E., Conrado, R. C. G., Campos, L. de O., Olivatto, M. M., Gutierrez, M. A., Traina Junior, C., et al. (2025). Modeling clinical data with attention: a knowledge graph approach with CliniKG. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS65348.2025.00156
NLM
Moura E, Conrado RCG, Campos L de O, Olivatto MM, Gutierrez MA, Traina Junior C, Traina AJM, Cazzolato MT. Modeling clinical data with attention: a knowledge graph approach with CliniKG [Internet]. Proceedings. 2025 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00156
Vancouver
Moura E, Conrado RCG, Campos L de O, Olivatto MM, Gutierrez MA, Traina Junior C, Traina AJM, Cazzolato MT. Modeling clinical data with attention: a knowledge graph approach with CliniKG [Internet]. Proceedings. 2025 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00156
Trabalho de evento
FairMed-FL: federated learning for fair and unbiased deep learning in medical imaging (2025)
Carmo, Êrica Peters do ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZAGEM PROFUNDA, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR IMAGEM
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ABNT
CARMO, Êrica Peters do e TRAINA JUNIOR, Caetano e TRAINA, Agma Juci Machado. FairMed-FL: federated learning for fair and unbiased deep learning in medical imaging. 2025, Anais.. Los Alamitos: IEEE, 2025. Disponível em: https://doi.org/10.1109/CBMS65348.2025.00158. Acesso em: 29 nov. 2025.
APA
Carmo, Ê. P. do, Traina Junior, C., & Traina, A. J. M. (2025). FairMed-FL: federated learning for fair and unbiased deep learning in medical imaging. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS65348.2025.00158
NLM
Carmo ÊP do, Traina Junior C, Traina AJM. FairMed-FL: federated learning for fair and unbiased deep learning in medical imaging [Internet]. Proceedings. 2025 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00158
Vancouver
Carmo ÊP do, Traina Junior C, Traina AJM. FairMed-FL: federated learning for fair and unbiased deep learning in medical imaging [Internet]. Proceedings. 2025 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS65348.2025.00158
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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] 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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] 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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] Available from: https://doi.org/10.1145/3605098.3636019
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
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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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS61543.2024.00078
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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS61543.2024.00050
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
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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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] 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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
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
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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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] 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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] 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
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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: 29 nov. 2025.
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 2025 nov. 29 ] 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 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS55023.2022.00021
Trabalho de evento
BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging (2021)
Ramos, Jonathan da Silva ; 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, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, RESSONÂNCIA MAGNÉTICA, DENSITOMETRIA ÓSSEA, OSTEOPOROSE, FRATURAS, VÉRTEBRAS LOMBARES
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ABNT
RAMOS, Jonathan da Silva et al. BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00089. Acesso em: 29 nov. 2025.
APA
Ramos, J. da S., Maciel, J. G., Cazzolato, M. T., Traina Junior, C., Nogueira-Barbosa, M. H., & Traina, A. J. M. (2021). BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00089
NLM
Ramos J da S, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00089
Vancouver
Ramos J da S, Maciel JG, Cazzolato MT, Traina Junior C, Nogueira-Barbosa MH, Traina AJM. BEAUT: a radiomic approach to identify potential lumbar fractures in magnetic resonance imaging [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00089
Trabalho de evento
Multilevel clustering explainer: an explainable approach to electronic health records (2021)
Clementino Jr, José Maria ; Faiçal, Bruno Squizato ; Bones, Christian Cesar ; Traina Junior, Caetano ; Gutierrez, Marco Antonio ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, DESCOBERTA DE CONHECIMENTO, TECNOLOGIAS DA SAÚDE
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ABNT
CLEMENTINO JR, José Maria et al. Multilevel clustering explainer: an explainable approach to electronic health records. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00073. Acesso em: 29 nov. 2025.
APA
Clementino Jr, J. M., Faiçal, B. S., Bones, C. C., Traina Junior, C., Gutierrez, M. A., & Traina, A. J. M. (2021). Multilevel clustering explainer: an explainable approach to electronic health records. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00073
NLM
Clementino Jr JM, Faiçal BS, Bones CC, Traina Junior C, Gutierrez MA, Traina AJM. Multilevel clustering explainer: an explainable approach to electronic health records [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00073
Vancouver
Clementino Jr JM, Faiçal BS, Bones CC, Traina Junior C, Gutierrez MA, Traina AJM. Multilevel clustering explainer: an explainable approach to electronic health records [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00073
Trabalho de evento
VD-Tree: how to build an efficient and fit metric access method using Voronoi diagrams (2021)
Moriyama, André Toshio Asanome; Rodrigues, Lucas Santiago ; Scabora, Lucas de Carvalho ; Cazzolato, Mirela Teixeira ; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Proceedings. Conference titles: Symposium on Applied Computing - SAC. Unidade: ICMC
Subjects: ESTRUTURAS DE DADOS, RECUPERAÇÃO DA INFORMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MORIYAMA, André Toshio Asanome et al. VD-Tree: how to build an efficient and fit metric access method using Voronoi diagrams. 2021, Anais.. New York: ACM, 2021. Disponível em: https://doi.org/10.1145/3412841.3441915. Acesso em: 29 nov. 2025.
APA
Moriyama, A. T. A., Rodrigues, L. S., Scabora, L. de C., Cazzolato, M. T., Traina, A. J. M., & Traina Junior, C. (2021). VD-Tree: how to build an efficient and fit metric access method using Voronoi diagrams. In Proceedings. New York: ACM. doi:10.1145/3412841.3441915
NLM
Moriyama ATA, Rodrigues LS, Scabora L de C, Cazzolato MT, Traina AJM, Traina Junior C. VD-Tree: how to build an efficient and fit metric access method using Voronoi diagrams [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1145/3412841.3441915
Vancouver
Moriyama ATA, Rodrigues LS, Scabora L de C, Cazzolato MT, Traina AJM, Traina Junior C. VD-Tree: how to build an efficient and fit metric access method using Voronoi diagrams [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1145/3412841.3441915
Trabalho de evento
I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs (2021)
Linhares, Claudio Douglas Gouveia ; Lima, Daniel Mário de ; Bones, Christian Cesar ; Rebelo, Marina F. S; Gutierrez, Marco Antonio ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: BANCO DE DADOS, VISUALIZAÇÃO, MINERAÇÃO DE DADOS, REDES COMPLEXAS, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LINHARES, Claudio Douglas Gouveia et al. I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00059. Acesso em: 29 nov. 2025.
APA
Linhares, C. D. G., Lima, D. M. de, Bones, C. C., Rebelo, M. F. S., Gutierrez, M. A., Traina Junior, C., & Traina, A. J. M. (2021). I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00059
NLM
Linhares CDG, Lima DM de, Bones CC, Rebelo MFS, Gutierrez MA, Traina Junior C, Traina AJM. I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00059
Vancouver
Linhares CDG, Lima DM de, Bones CC, Rebelo MFS, Gutierrez MA, Traina Junior C, Traina AJM. I-CovidVis: a visual analytics tool for interoperable healthcare databases using graphs [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00059
Trabalho de evento
SHARq: sharing recursive queries in relational databases (2021)
Scabora, Lucas de Carvalho ; Spadon, Gabriel ; Cazzolato, Mirela Teixeira ; Kaster, Daniel dos Santos ; Traina, Agma Juci Machado ; Rodrigues Junior, José Fernando ; Traina Junior, Caetano
Source: Proceedings. Conference titles: Symposium on Applied Computing - SAC. Unidade: ICMC
Subjects: GERENCIADORES DE BANCO DE DADOS, BANCO DE DADOS RELACIONAIS, RECUPERAÇÃO DA INFORMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SCABORA, Lucas de Carvalho et al. SHARq: sharing recursive queries in relational databases. 2021, Anais.. New York: ACM, 2021. Disponível em: https://doi.org/10.1145/3412841.3442078. Acesso em: 29 nov. 2025.
APA
Scabora, L. de C., Spadon, G., Cazzolato, M. T., Kaster, D. dos S., Traina, A. J. M., Rodrigues Junior, J. F., & Traina Junior, C. (2021). SHARq: sharing recursive queries in relational databases. In Proceedings. New York: ACM. doi:10.1145/3412841.3442078
NLM
Scabora L de C, Spadon G, Cazzolato MT, Kaster D dos S, Traina AJM, Rodrigues Junior JF, Traina Junior C. SHARq: sharing recursive queries in relational databases [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1145/3412841.3442078
Vancouver
Scabora L de C, Spadon G, Cazzolato MT, Kaster D dos S, Traina AJM, Rodrigues Junior JF, Traina Junior C. SHARq: sharing recursive queries in relational databases [Internet]. Proceedings. 2021 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1145/3412841.3442078
Trabalho de evento
Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP (2020)
Clementino Jr, José Maria ; Bones, Christian Cesar ; Faiçal, Bruno Squizato ; Linares, Oscar Alonso Cuadros ; Lima, Daniel Mário de ; Gutierrez, Marco A; 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, SISTEMAS DE INFORMAÇÃO HOSPITALAR, DESCOBERTA DE CONHECIMENTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CLEMENTINO JR, José Maria et al. Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00045. Acesso em: 29 nov. 2025.
APA
Clementino Jr, J. M., Bones, C. C., Faiçal, B. S., Linares, O. A. C., Lima, D. M. de, Gutierrez, M. A., et al. (2020). Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00045
NLM
Clementino Jr JM, Bones CC, Faiçal BS, Linares OAC, Lima DM de, Gutierrez MA, Traina Junior C, Traina AJM. Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP [Internet]. Proceedings. 2020 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00045
Vancouver
Clementino Jr JM, Bones CC, Faiçal BS, Linares OAC, Lima DM de, Gutierrez MA, Traina Junior C, Traina AJM. Bag-of-attributes representation: a vector space model for electronic health records analysis in OMOP [Internet]. Proceedings. 2020 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00045
Trabalho de evento
Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine (2020)
Cazzolato, Mirela Teixeira ; Ramos, Jonathan da Silva ; Rodrigues, Lucas Santiago ; Scabora, Lucas de Carvalho ; Chino, Daniel Yoshinobu Takada ; Jorge, Ana Elisa Serafim ; Azevedo-Marques, Paulo Mazzoncini de ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FMRP, ICMC
Subjects: COMPUTAÇÃO MÓVEL, PROCESSAMENTO DE IMAGENS, ÚLCERA CUTÂNEA, TECNOLOGIAS DA SAÚDE, TELEMEDICINA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00073. Acesso em: 29 nov. 2025.
APA
Cazzolato, M. T., Ramos, J. da S., Rodrigues, L. S., Scabora, L. de C., Chino, D. Y. T., Jorge, A. E. S., et al. (2020). Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00073
NLM
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073
Vancouver
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073
Trabalho de evento
Enhancing recursive graph querying on RDBMS with data clustering approaches (2020)
Scabora, Lucas de Carvalho ; Spadon, Gabriel ; Oliveira, Paulo Henrique de ; Rodrigues Junior, José Fernando ; Traina Junior, Caetano
Source: Proceedings. Conference titles: ACM/SIGAPP Symposium on Applied Computing - SAC. Unidade: ICMC
Subjects: BANCO DE DADOS, CLUSTERS, LÓGICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SCABORA, Lucas de Carvalho et al. Enhancing recursive graph querying on RDBMS with data clustering approaches. 2020, Anais.. New York: ACM, 2020. Disponível em: https://doi.org/10.1145/3341105.3375770. Acesso em: 29 nov. 2025.
APA
Scabora, L. de C., Spadon, G., Oliveira, P. H. de, Rodrigues Junior, J. F., & Traina Junior, C. (2020). Enhancing recursive graph querying on RDBMS with data clustering approaches. In Proceedings. New York: ACM. doi:10.1145/3341105.3375770
NLM
Scabora L de C, Spadon G, Oliveira PH de, Rodrigues Junior JF, Traina Junior C. Enhancing recursive graph querying on RDBMS with data clustering approaches [Internet]. Proceedings. 2020 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1145/3341105.3375770
Vancouver
Scabora L de C, Spadon G, Oliveira PH de, Rodrigues Junior JF, Traina Junior C. Enhancing recursive graph querying on RDBMS with data clustering approaches [Internet]. Proceedings. 2020 ;[citado 2025 nov. 29 ] Available from: https://doi.org/10.1145/3341105.3375770

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