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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: 09 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. 09 ] 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. 09 ] 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: 09 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. 09 ] 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. 09 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00202
Trabalho de evento
Hemoglobin estimation from smartphone-based photoplethysmography with small data (2023)
Silva, Diego Furtado ; Medeiros Júnior, José Gilberto Barbosa de; Domingues, Lucas Vinícius ; Mazzu-Nascimento, Thiago
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE DE SÉRIES TEMPORAIS, HEMOGLOBINAS, TECNOLOGIAS DA SAÚDE
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ABNT
SILVA, Diego Furtado et al. Hemoglobin estimation from smartphone-based photoplethysmography with small data. 2023, Anais.. Los Alamitos: IEEE, 2023. Disponível em: https://doi.org/10.1109/CBMS58004.2023.00195. Acesso em: 09 out. 2024.
APA
Silva, D. F., Medeiros Júnior, J. G. B. de, Domingues, L. V., & Mazzu-Nascimento, T. (2023). Hemoglobin estimation from smartphone-based photoplethysmography with small data. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS58004.2023.00195
NLM
Silva DF, Medeiros Júnior JGB de, Domingues LV, Mazzu-Nascimento T. Hemoglobin estimation from smartphone-based photoplethysmography with small data [Internet]. Proceedings. 2023 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00195
Vancouver
Silva DF, Medeiros Júnior JGB de, Domingues LV, Mazzu-Nascimento T. Hemoglobin estimation from smartphone-based photoplethysmography with small data [Internet]. Proceedings. 2023 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS58004.2023.00195
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: 09 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. 09 ] 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. 09 ] 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: 09 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. 09 ] 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. 09 ] 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: 09 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. 09 ] 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. 09 ] 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: 09 out. 2024.
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 2024 out. 09 ] 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 2024 out. 09 ] 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: 09 out. 2024.
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 2024 out. 09 ] 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 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00073
Trabalho de evento
APEHR: automated prognosis in electronic health records using multi-head self-attention (2021)
Florez, Alexander Ylnner Choquenaira ; Scabora, Lucas de Carvalho ; Eler, Danilo Medeiros ; Rodrigues Junior, José Fernando
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, TECNOLOGIAS DA SAÚDE, PROGNÓSTICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FLOREZ, Alexander Ylnner Choquenaira et al. APEHR: automated prognosis in electronic health records using multi-head self-attention. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00077. Acesso em: 09 out. 2024.
APA
Florez, A. Y. C., Scabora, L. de C., Eler, D. M., & Rodrigues Junior, J. F. (2021). APEHR: automated prognosis in electronic health records using multi-head self-attention. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00077
NLM
Florez AYC, Scabora L de C, Eler DM, Rodrigues Junior JF. APEHR: automated prognosis in electronic health records using multi-head self-attention [Internet]. Proceedings. 2021 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00077
Vancouver
Florez AYC, Scabora L de C, Eler DM, Rodrigues Junior JF. APEHR: automated prognosis in electronic health records using multi-head self-attention [Internet]. Proceedings. 2021 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00077
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: 09 out. 2024.
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 2024 out. 09 ] 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 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00059
Trabalho de evento
A two-phase learning approach for the segmentation of dermatological wounds (2019)
Silva, Wellington S; Jasbick, Daniel L ; Wilson, Rodrigo E; Azevedo-Marques, Paulo Mazzoncini de ; Traina, Agma Juci Machado ; Santos, Lúcio F. D; Jorge, Ana Elisa Serafim ; Oliveira, Daniel de; Bêdo, Marcos Vinícius Naves
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FMRP, ICMC
Subjects: PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, ÚLCERA CUTÂNEA
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ABNT
SILVA, Wellington S et al. A two-phase learning approach for the segmentation of dermatological wounds. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00076. Acesso em: 09 out. 2024.
APA
Silva, W. S., Jasbick, D. L., Wilson, R. E., Azevedo-Marques, P. M. de, Traina, A. J. M., Santos, L. F. D., et al. (2019). A two-phase learning approach for the segmentation of dermatological wounds. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00076
NLM
Silva WS, Jasbick DL, Wilson RE, Azevedo-Marques PM de, Traina AJM, Santos LFD, Jorge AES, Oliveira D de, Bêdo MVN. A two-phase learning approach for the segmentation of dermatological wounds [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00076
Vancouver
Silva WS, Jasbick DL, Wilson RE, Azevedo-Marques PM de, Traina AJM, Santos LFD, Jorge AES, Oliveira D de, Bêdo MVN. A two-phase learning approach for the segmentation of dermatological wounds [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00076
Trabalho de evento
How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis (2019)
Linares, Oscar Alonso Cuadros ; Faiçal, Bruno Squizato ; Barbosa, Paulo Renato Campos; Hamann, Bernd; Fabro, Alexandre Todorovic ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FMRP, ICMC
Subjects: PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, DOENÇAS PULMONARES INTERSTICIAIS
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ABNT
LINARES, Oscar Alonso Cuadros et al. How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00118. Acesso em: 09 out. 2024.
APA
Linares, O. A. C., Faiçal, B. S., Barbosa, P. R. C., Hamann, B., Fabro, A. T., & Traina, A. J. M. (2019). How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00118
NLM
Linares OAC, Faiçal BS, Barbosa PRC, Hamann B, Fabro AT, Traina AJM. How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00118
Vancouver
Linares OAC, Faiçal BS, Barbosa PRC, Hamann B, Fabro AT, Traina AJM. How to automatically identify regions of interest in high-resolution images of lung biopsy for interstitial fibrosis diagnosis [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00118
Trabalho de evento
3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging (2019)
Ramos, Jonathan da Silva; Cazzolato, Mirela Teixeira ; Faiçal, Bruno Squizato ; Nogueira-Barbosa, Marcello Henrique ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FMRP, ICMC
Subjects: PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, RESSONÂNCIA MAGNÉTICA, COMPREENSÃO VERBAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RAMOS, Jonathan da Silva et al. 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00091. Acesso em: 09 out. 2024.
APA
Ramos, J. da S., Cazzolato, M. T., Faiçal, B. S., Nogueira-Barbosa, M. H., Traina Junior, C., & Traina, A. J. M. (2019). 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00091
NLM
Ramos J da S, Cazzolato MT, Faiçal BS, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00091
Vancouver
Ramos J da S, Cazzolato MT, Faiçal BS, Nogueira-Barbosa MH, Traina Junior C, Traina AJM. 3DBGrowth: volumetric vertebrae segmentation and reconstruction in magnetic resonance imaging [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00091
Trabalho de evento
UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images (2019)
Zabot, Guilherme Felipe ; Cazzolato, Mirela Teixeira ; Scabora, Lucas de Carvalho ; Faiçal, Bruno Squizato ; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: RECUPERAÇÃO DA INFORMAÇÃO, BANCO DE DADOS MULTIMÍDIA, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ZABOT, Guilherme Felipe et al. UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/CBMS.2019.00070. Acesso em: 09 out. 2024.
APA
Zabot, G. F., Cazzolato, M. T., Scabora, L. de C., Faiçal, B. S., Traina, A. J. M., & Traina Junior, C. (2019). UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2019.00070
NLM
Zabot GF, Cazzolato MT, Scabora L de C, Faiçal BS, Traina AJM, Traina Junior C. UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00070
Vancouver
Zabot GF, Cazzolato MT, Scabora L de C, Faiçal BS, Traina AJM, Traina Junior C. UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images [Internet]. Proceedings. 2019 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2019.00070
Trabalho de evento
ICARUS: retrieving skin ulcer images through bag-of-signatures (2018)
Chino, Daniel Y. T; Scabora, Lucas C; Cazzolato, Mirela T; Jorge, Ana E. S; 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 MULTIMÍDIA, RECUPERAÇÃO DA INFORMAÇÃO, ÚLCERA CUTÂNEA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHINO, Daniel Y. T et al. ICARUS: retrieving skin ulcer images through bag-of-signatures. 2018, Anais.. Los Alamitos: IEEE, 2018. Disponível em: https://doi.org/10.1109/CBMS.2018.00022. Acesso em: 09 out. 2024.
APA
Chino, D. Y. T., Scabora, L. C., Cazzolato, M. T., Jorge, A. E. S., Traina Junior, C., & Traina, A. J. M. (2018). ICARUS: retrieving skin ulcer images through bag-of-signatures. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2018.00022
NLM
Chino DYT, Scabora LC, Cazzolato MT, Jorge AES, Traina Junior C, Traina AJM. ICARUS: retrieving skin ulcer images through bag-of-signatures [Internet]. Proceedings. 2018 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2018.00022
Vancouver
Chino DYT, Scabora LC, Cazzolato MT, Jorge AES, Traina Junior C, Traina AJM. ICARUS: retrieving skin ulcer images through bag-of-signatures [Internet]. Proceedings. 2018 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2018.00022
Trabalho de evento
RAFIKI: retrieval-based application for imaging and knowledge investigation (2018)
Nesso-Jr, Marcos R; Cazzolato, Mirela T; Scabora, Lucas C; Oliveira, Paulo H; Spadon, Gabriel; Souza, Jessica A. de; Oliveira, Willian Dener de; Chino, Daniel Y. T; Rodrigues Junior, José Fernando ; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: BANCO DE DADOS MULTIMÍDIA, RECUPERAÇÃO DA INFORMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NESSO-JR, Marcos R et al. RAFIKI: retrieval-based application for imaging and knowledge investigation. 2018, Anais.. Los Alamitos: IEEE, 2018. Disponível em: https://doi.org/10.1109/CBMS.2018.00020. Acesso em: 09 out. 2024.
APA
Nesso-Jr, M. R., Cazzolato, M. T., Scabora, L. C., Oliveira, P. H., Spadon, G., Souza, J. A. de, et al. (2018). RAFIKI: retrieval-based application for imaging and knowledge investigation. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2018.00020
NLM
Nesso-Jr MR, Cazzolato MT, Scabora LC, Oliveira PH, Spadon G, Souza JA de, Oliveira WD de, Chino DYT, Rodrigues Junior JF, Traina AJM, Traina Junior C. RAFIKI: retrieval-based application for imaging and knowledge investigation [Internet]. Proceedings. 2018 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2018.00020
Vancouver
Nesso-Jr MR, Cazzolato MT, Scabora LC, Oliveira PH, Spadon G, Souza JA de, Oliveira WD de, Chino DYT, Rodrigues Junior JF, Traina AJM, Traina Junior C. RAFIKI: retrieval-based application for imaging and knowledge investigation [Internet]. Proceedings. 2018 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2018.00020
Trabalho de evento
Anomaly detection through temporal abstractions on intensive care data: position paper (2017)
Gelatti, Giovana Jaskulski; Carvalho, André Carlos Ponce de Leon Ferreira de ; Rodrigues, Pedro Pereira
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ANÁLISE DE SÉRIES TEMPORAIS, COMPUTAÇÃO APLICADA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GELATTI, Giovana Jaskulski e CARVALHO, André Carlos Ponce de Leon Ferreira de e RODRIGUES, Pedro Pereira. Anomaly detection through temporal abstractions on intensive care data: position paper. 2017, Anais.. Los Alamitos: IEEE, 2017. Disponível em: https://doi.org/10.1109/CBMS.2017.146. Acesso em: 09 out. 2024.
APA
Gelatti, G. J., Carvalho, A. C. P. de L. F. de, & Rodrigues, P. P. (2017). Anomaly detection through temporal abstractions on intensive care data: position paper. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2017.146
NLM
Gelatti GJ, Carvalho ACP de LF de, Rodrigues PP. Anomaly detection through temporal abstractions on intensive care data: position paper [Internet]. Proceedings. 2017 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2017.146
Vancouver
Gelatti GJ, Carvalho ACP de LF de, Rodrigues PP. Anomaly detection through temporal abstractions on intensive care data: position paper [Internet]. Proceedings. 2017 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2017.146
Trabalho de evento
BREATH: heat maps assisting the detection of abnormal lung regions in CT Scans (2017)
Cazzolato, Mirela T; Scabora, Lucas C; Costa, Alceu F; Nesso-Jr, Marcos R; Milano-Oliveira, Luis F; Kaster, Daniel S; 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, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, DIAGNÓSTICO POR IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela T et al. BREATH: heat maps assisting the detection of abnormal lung regions in CT Scans. 2017, Anais.. Los Alamitos: IEEE, 2017. Disponível em: https://doi.org/10.1109/CBMS.2017.82. Acesso em: 09 out. 2024.
APA
Cazzolato, M. T., Scabora, L. C., Costa, A. F., Nesso-Jr, M. R., Milano-Oliveira, L. F., Kaster, D. S., et al. (2017). BREATH: heat maps assisting the detection of abnormal lung regions in CT Scans. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2017.82
NLM
Cazzolato MT, Scabora LC, Costa AF, Nesso-Jr MR, Milano-Oliveira LF, Kaster DS, Traina Junior C, Traina AJM. BREATH: heat maps assisting the detection of abnormal lung regions in CT Scans [Internet]. Proceedings. 2017 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2017.82
Vancouver
Cazzolato MT, Scabora LC, Costa AF, Nesso-Jr MR, Milano-Oliveira LF, Kaster DS, Traina Junior C, Traina AJM. BREATH: heat maps assisting the detection of abnormal lung regions in CT Scans [Internet]. Proceedings. 2017 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2017.82
Trabalho de evento
Efficiently indexing multiple repositories of medical image databases (2017)
Oliveira, Paulo H; Scabora, Lucas C; Cazzolato, Mirela T; Oliveira, Willian Dener de; Traina, Agma Juci Machado ; Traina Junior, Caetano
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: BANCO DE DADOS, PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Paulo H et al. Efficiently indexing multiple repositories of medical image databases. 2017, Anais.. Los Alamitos: IEEE, 2017. Disponível em: https://doi.org/10.1109/CBMS.2017.81. Acesso em: 09 out. 2024.
APA
Oliveira, P. H., Scabora, L. C., Cazzolato, M. T., Oliveira, W. D. de, Traina, A. J. M., & Traina Junior, C. (2017). Efficiently indexing multiple repositories of medical image databases. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2017.81
NLM
Oliveira PH, Scabora LC, Cazzolato MT, Oliveira WD de, Traina AJM, Traina Junior C. Efficiently indexing multiple repositories of medical image databases [Internet]. Proceedings. 2017 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2017.81
Vancouver
Oliveira PH, Scabora LC, Cazzolato MT, Oliveira WD de, Traina AJM, Traina Junior C. Efficiently indexing multiple repositories of medical image databases [Internet]. Proceedings. 2017 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2017.81
Trabalho de evento
Automatic proposition extraction from dependency trees: helping early prediction of Alzheimer's disease from narratives (2015)
Cunha, André Luiz V. da; Sousa, Luciene Bender de; Mansur, Letícia Lessa; Aluísio, Sandra Maria
Source: Proceedings. Conference titles: International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FM, ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, PROCESSAMENTO DE LINGUAGEM NATURAL, COMPUTAÇÃO APLICADA, DOENÇA DE ALZHEIMER
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CUNHA, André Luiz V. da et al. Automatic proposition extraction from dependency trees: helping early prediction of Alzheimer's disease from narratives. 2015, Anais.. Los Alamitos: IEEE, 2015. Disponível em: https://doi.org/10.1109/CBMS.2015.19. Acesso em: 09 out. 2024.
APA
Cunha, A. L. V. da, Sousa, L. B. de, Mansur, L. L., & Aluísio, S. M. (2015). Automatic proposition extraction from dependency trees: helping early prediction of Alzheimer's disease from narratives. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS.2015.19
NLM
Cunha ALV da, Sousa LB de, Mansur LL, Aluísio SM. Automatic proposition extraction from dependency trees: helping early prediction of Alzheimer's disease from narratives [Internet]. Proceedings. 2015 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2015.19
Vancouver
Cunha ALV da, Sousa LB de, Mansur LL, Aluísio SM. Automatic proposition extraction from dependency trees: helping early prediction of Alzheimer's disease from narratives [Internet]. Proceedings. 2015 ;[citado 2024 out. 09 ] Available from: https://doi.org/10.1109/CBMS.2015.19

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