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Artigo de periodico
ClinicalPath: a visualization tool to improve the evaluation of electronic health records in clinical decision-making (2022)
Linhares, Claudio Douglas Gouveia ; Lima, Daniel Mário de ; Ponciano, Jean Roberto ; Olivatto, Mauro M; Gutierrez, Marco Antonio ; Poco, Jorge ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: IEEE Transactions on Visualization and Computer Graphics. Unidades: EP, 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, 2022Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2022.3175626. Acesso em: 12 ago. 2022.
APA
Linhares, C. D. G., Lima, D. M. de, Ponciano, J. R., Olivatto, M. M., Gutierrez, M. A., Poco, J., et al. (2022). ClinicalPath: a visualization tool to improve the evaluation of electronic health records in clinical decision-making. IEEE Transactions on Visualization and Computer Graphics. 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. 2022 ;[citado 2022 ago. 12 ] 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. 2022 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/TVCG.2022.3175626
Artigo de periodico
Pay attention to evolution: time series forecasting with deep graph-evolution learning (2021)
Spadon, Gabriel ; Sun, Jimeng ; Hong, Shenda ; Machado, Bruno Brandoli ; Matwin, Stan ; Rodrigues Junior, José Fernando
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. Unidade: ICMC
Subjects: PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), APRENDIZADO COMPUTACIONAL, REDES NEURAIS, TEORIA DOS GRAFOS
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ABNT
SPADON, Gabriel et al. Pay attention to evolution: time series forecasting with deep graph-evolution learning. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM, 2021Tradução . . Disponível em: https://doi.org/10.1109/TPAMI.2021.3076155. Acesso em: 12 ago. 2022.
APA
Spadon, G., Sun, J., Hong, S., Machado, B. B., Matwin, S., & Rodrigues Junior, J. F. (2021). Pay attention to evolution: time series forecasting with deep graph-evolution learning. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. doi:10.1109/TPAMI.2021.3076155
NLM
Spadon G, Sun J, Hong S, Machado BB, Matwin S, Rodrigues Junior JF. Pay attention to evolution: time series forecasting with deep graph-evolution learning [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/TPAMI.2021.3076155
Vancouver
Spadon G, Sun J, Hong S, Machado BB, Matwin S, Rodrigues Junior JF. Pay attention to evolution: time series forecasting with deep graph-evolution learning [Internet]. IEEE Transactions on Pattern Analysis and Machine Intelligence - TPAM. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/TPAMI.2021.3076155
Trabalho de evento
Supporting IoT-based applications to combat the Aedes aegypti mosquito: a case in Brazil (2021)
Silva, Henrique de Araújo; Adriano, Elias; Scatolini, Denise ; Braga, Rosana Teresinha Vaccare
Source: Proceedings. Conference title: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: MOSQUITOS, INTERNET DAS COISAS, SAÚDE PÚBLICA
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ABNT
SILVA, Henrique de Araújo et al. Supporting IoT-based applications to combat the Aedes aegypti mosquito: a case in Brazil. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/CBMS52027.2021.00029. Acesso em: 12 ago. 2022.
APA
Silva, H. de A., Adriano, E., Scatolini, D., & Braga, R. T. V. (2021). Supporting IoT-based applications to combat the Aedes aegypti mosquito: a case in Brazil. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS52027.2021.00029
NLM
Silva H de A, Adriano E, Scatolini D, Braga RTV. Supporting IoT-based applications to combat the Aedes aegypti mosquito: a case in Brazil [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00029
Vancouver
Silva H de A, Adriano E, Scatolini D, Braga RTV. Supporting IoT-based applications to combat the Aedes aegypti mosquito: a case in Brazil [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00029
Trabalho de evento
Training deep networks from zero to hero: avoiding pitfalls and going beyond (2021)
Ponti, Moacir Antonelli ; Santos, Fernando Pereira dos ; Ribeiro, Leo Sampaio Ferraz ; Cavallari, Gabriel Biscaro
Source: Proceedings. Conference title: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: ICMC
Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM
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ABNT
PONTI, Moacir Antonelli et al. Training deep networks from zero to hero: avoiding pitfalls and going beyond. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00011. Acesso em: 12 ago. 2022.
APA
Ponti, M. A., Santos, F. P. dos, Ribeiro, L. S. F., & Cavallari, G. B. (2021). Training deep networks from zero to hero: avoiding pitfalls and going beyond. In Proceedings. Los Alamitos: IEEE. doi:10.1109/SIBGRAPI54419.2021.00011
NLM
Ponti MA, Santos FP dos, Ribeiro LSF, Cavallari GB. Training deep networks from zero to hero: avoiding pitfalls and going beyond [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00011
Vancouver
Ponti MA, Santos FP dos, Ribeiro LSF, Cavallari GB. Training deep networks from zero to hero: avoiding pitfalls and going beyond [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00011
Trabalho de evento
Fast and lightweight binary and multi-branch Hoeffding tree regressors (2021)
Mastelini, Saulo Martiello ; Montiel, Jacob ; Gomes, Heitor Murilo ; Bifet, Albert ; Pfahringer, Bernhard ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Source: Proceedings. Conference title: International Conference on Data Mining Workshops - ICDMW. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES
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ABNT
MASTELINI, Saulo Martiello et al. Fast and lightweight binary and multi-branch Hoeffding tree regressors. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICDMW53433.2021.00053. Acesso em: 12 ago. 2022.
APA
Mastelini, S. M., Montiel, J., Gomes, H. M., Bifet, A., Pfahringer, B., & Carvalho, A. C. P. de L. F. de. (2021). Fast and lightweight binary and multi-branch Hoeffding tree regressors. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICDMW53433.2021.00053
NLM
Mastelini SM, Montiel J, Gomes HM, Bifet A, Pfahringer B, Carvalho ACP de LF de. Fast and lightweight binary and multi-branch Hoeffding tree regressors [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICDMW53433.2021.00053
Vancouver
Mastelini SM, Montiel J, Gomes HM, Bifet A, Pfahringer B, Carvalho ACP de LF de. Fast and lightweight binary and multi-branch Hoeffding tree regressors [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICDMW53433.2021.00053
Trabalho de evento
Modeling students' flow experience through data logs in gamified educational systems (2021)
Santos, Wilk Oliveira dos ; Isotani, Seiji ; Pastushenko, Olena ; Hruška, Tomáš ; Hamari, Juho
Source: Proceedings. Conference title: International Conference on Advanced Learning Technologies - ICALT. Unidade: ICMC
Subjects: JOGOS DE COMPUTADOR, JOGADORES, EDUCAÇÃO
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ABNT
SANTOS, Wilk Oliveira dos et al. Modeling students' flow experience through data logs in gamified educational systems. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICALT52272.2021.00037. Acesso em: 12 ago. 2022.
APA
Santos, W. O. dos, Isotani, S., Pastushenko, O., Hruška, T., & Hamari, J. (2021). Modeling students' flow experience through data logs in gamified educational systems. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICALT52272.2021.00037
NLM
Santos WO dos, Isotani S, Pastushenko O, Hruška T, Hamari J. Modeling students' flow experience through data logs in gamified educational systems [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICALT52272.2021.00037
Vancouver
Santos WO dos, Isotani S, Pastushenko O, Hruška T, Hamari J. Modeling students' flow experience through data logs in gamified educational systems [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICALT52272.2021.00037
Trabalho de evento
TOVEC: task optimization mechanism for vehicular clouds using meta-heuristic technique (2021)
Lieira, Douglas Dias ; Quessada, Matheus Sanches ; Costa, Joahannes Bruno Dias da ; Cerqueira, Eduardo ; Rosário, Denis Lima ; Meneguette, Rodolfo Ipolito
Source: Proceedings. Conference title: International Wireless Communications and Mobile Computing - IWCMC. Unidade: ICMC
Subjects: SISTEMAS INTELIGENTES DE TRANSPORTES, ALOCAÇÃO DE RECURSOS, ALGORITMOS ÚTEIS E ESPECÍFICOS
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ABNT
LIEIRA, Douglas Dias et al. TOVEC: task optimization mechanism for vehicular clouds using meta-heuristic technique. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/IWCMC51323.2021.9498784. Acesso em: 12 ago. 2022.
APA
Lieira, D. D., Quessada, M. S., Costa, J. B. D. da, Cerqueira, E., Rosário, D. L., & Meneguette, R. I. (2021). TOVEC: task optimization mechanism for vehicular clouds using meta-heuristic technique. In Proceedings. Los Alamitos: IEEE. doi:10.1109/IWCMC51323.2021.9498784
NLM
Lieira DD, Quessada MS, Costa JBD da, Cerqueira E, Rosário DL, Meneguette RI. TOVEC: task optimization mechanism for vehicular clouds using meta-heuristic technique [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/IWCMC51323.2021.9498784
Vancouver
Lieira DD, Quessada MS, Costa JBD da, Cerqueira E, Rosário DL, Meneguette RI. TOVEC: task optimization mechanism for vehicular clouds using meta-heuristic technique [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/IWCMC51323.2021.9498784
Trabalho de evento
Graph restrictions for signal processing of homicides data (2021)
Soto, Sebastian Quintero; Pabon, Juan S. Moreno; Rubio, Mateo Dulce; Riascos, Alvaro J ; Nonato, Luis Gustavo
Source: Proceedings. Conference title: International Conference on Applied Artificial Intelligence - ICAPAI. Unidade: ICMC
Subjects: HOMICÍDIO, PROCESSAMENTO DE SINAIS, CRIMINALIDADE
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ABNT
SOTO, Sebastian Quintero et al. Graph restrictions for signal processing of homicides data. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICAPAI49758.2021.9462063. Acesso em: 12 ago. 2022.
APA
Soto, S. Q., Pabon, J. S. M., Rubio, M. D., Riascos, A. J., & Nonato, L. G. (2021). Graph restrictions for signal processing of homicides data. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICAPAI49758.2021.9462063
NLM
Soto SQ, Pabon JSM, Rubio MD, Riascos AJ, Nonato LG. Graph restrictions for signal processing of homicides data [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICAPAI49758.2021.9462063
Vancouver
Soto SQ, Pabon JSM, Rubio MD, Riascos AJ, Nonato LG. Graph restrictions for signal processing of homicides data [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICAPAI49758.2021.9462063
Trabalho de evento
Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack (2021)
Cavallari, Gabriel Biscaro; Ponti, Moacir Antonelli
Source: Proceedings. Conference title: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM
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ABNT
CAVALLARI, Gabriel Biscaro e PONTI, Moacir Antonelli. Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00038. Acesso em: 12 ago. 2022.
APA
Cavallari, G. B., & Ponti, M. A. (2021). Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack. In Proceedings. Los Alamitos: IEEE. doi:10.1109/SIBGRAPI54419.2021.00038
NLM
Cavallari GB, Ponti MA. Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00038
Vancouver
Cavallari GB, Ponti MA. Semi-supervised siamese network using self-supervision under scarce annotation improves class separability and robustness to attack [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00038
Trabalho de evento
Business process analysis based on anomaly detection in event logs:: a study on an incident management case (2021)
Rojas Krugger, Esther Maria; Cárdenas Maita, Ana Rocío; Alves, Juliana Cristina Barbosa; Fantinato, Marcelo ; Peres, Sarajane Marques
Source: Proceedings. Conference title: Annual Hawaii International Conference on System Sciences (HICSS). Unidade: EACH
Subject: NEGÓCIOS
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ABNT
ROJAS KRUGGER, Esther Maria et al. Business process analysis based on anomaly detection in event logs:: a study on an incident management case. 2021, Anais.. Los Alamitos: IEEE Computer Society, 2021. Disponível em: https://doi.org/10.24251/HICSS.2021.130. Acesso em: 12 ago. 2022.
APA
Rojas Krugger, E. M., Cárdenas Maita, A. R., Alves, J. C. B., Fantinato, M., & Peres, S. M. (2021). Business process analysis based on anomaly detection in event logs:: a study on an incident management case. In Proceedings. Los Alamitos: IEEE Computer Society. doi:10.24251/HICSS.2021.130
NLM
Rojas Krugger EM, Cárdenas Maita AR, Alves JCB, Fantinato M, Peres SM. Business process analysis based on anomaly detection in event logs:: a study on an incident management case [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.24251/HICSS.2021.130
Vancouver
Rojas Krugger EM, Cárdenas Maita AR, Alves JCB, Fantinato M, Peres SM. Business process analysis based on anomaly detection in event logs:: a study on an incident management case [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.24251/HICSS.2021.130
Artigo de periodico
Explainable matrix: visualization for global and local interpretability of random forest classification ensembles (2021)
Popolin Neto, Mário ; Paulovich, Fernando Vieira
Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC
Subjects: VISUALIZAÇÃO, APRENDIZADO COMPUTACIONAL
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ABNT
POPOLIN NETO, Mário e PAULOVICH, Fernando Vieira. Explainable matrix: visualization for global and local interpretability of random forest classification ensembles. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 2, p. 1427-1437, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2020.3030354. Acesso em: 12 ago. 2022.
APA
Popolin Neto, M., & Paulovich, F. V. (2021). Explainable matrix: visualization for global and local interpretability of random forest classification ensembles. IEEE Transactions on Visualization and Computer Graphics, 27( 2), 1427-1437. doi:10.1109/TVCG.2020.3030354
NLM
Popolin Neto M, Paulovich FV. Explainable matrix: visualization for global and local interpretability of random forest classification ensembles [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 1427-1437.[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/TVCG.2020.3030354
Vancouver
Popolin Neto M, Paulovich FV. Explainable matrix: visualization for global and local interpretability of random forest classification ensembles [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 1427-1437.[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/TVCG.2020.3030354
Trabalho de evento
Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information (2021)
Silva, Júnior Anderson Rodrigues da ; Grassi Júnior, Valdir ; Wolf, Denis Fernando
Source: Proceedings. Conference title: International Conference on Advanced Robotics - ICAR. Unidades: EESC, ICMC
Subjects: VEÍCULOS AUTÔNOMOS, VISÃO COMPUTACIONAL, PROCESSOS DE MARKOV
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ABNT
SILVA, Júnior Anderson Rodrigues da e GRASSI JÚNIOR, Valdir e WOLF, Denis Fernando. Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICAR53236.2021.9659406. Acesso em: 12 ago. 2022.
APA
Silva, J. A. R. da, Grassi Júnior, V., & Wolf, D. F. (2021). Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICAR53236.2021.9659406
NLM
Silva JAR da, Grassi Júnior V, Wolf DF. Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICAR53236.2021.9659406
Vancouver
Silva JAR da, Grassi Júnior V, Wolf DF. Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICAR53236.2021.9659406
Trabalho de evento
Accurately quantifying under score variability (2021)
Maletzke, André Gustavo ; Reis, Denis Moreira dos ; Hassan, Waqar; Batista, Gustavo Enrique de Almeida Prado Alves
Source: Proceedings. Conference title: IEEE International Conference on Data Mining - ICDM. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, MINERAÇÃO DE DADOS
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ABNT
MALETZKE, André Gustavo et al. Accurately quantifying under score variability. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICDM51629.2021.00149. Acesso em: 12 ago. 2022.
APA
Maletzke, A. G., Reis, D. M. dos, Hassan, W., & Batista, G. E. de A. P. A. (2021). Accurately quantifying under score variability. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICDM51629.2021.00149
NLM
Maletzke AG, Reis DM dos, Hassan W, Batista GE de APA. Accurately quantifying under score variability [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICDM51629.2021.00149
Vancouver
Maletzke AG, Reis DM dos, Hassan W, Batista GE de APA. Accurately quantifying under score variability [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICDM51629.2021.00149
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 title: International Symposium on Computer-Based Medical Systems - CBMS. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, TECNOLOGIAS DA SAÚDE, PROGNÓSTICO
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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: 12 ago. 2022.
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 2022 ago. 12 ] 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 2022 ago. 12 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00077
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 title: 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: 12 ago. 2022.
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 2022 ago. 12 ] 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 2022 ago. 12 ] 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 title: 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: 12 ago. 2022.
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 2022 ago. 12 ] 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 2022 ago. 12 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00073
Trabalho de evento
DRIFT: a visual analytic tool for scientific literature exploration based on textual and image content (2021)
Pocco, Ximena; Poco, Jorge ; Paula, Rogerio de; Nonato, Luis Gustavo ; Gomez-Nieto, Erick Mauricio
Source: Proceedings. Conference title: Conference on Graphics, Patterns and Images - SIBGRAPI. Unidade: ICMC
Subjects: RECONHECIMENTO DE IMAGEM, VISUALIZAÇÃO, RECUPERAÇÃO DA INFORMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
POCCO, Ximena et al. DRIFT: a visual analytic tool for scientific literature exploration based on textual and image content. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/SIBGRAPI54419.2021.00027. Acesso em: 12 ago. 2022.
APA
Pocco, X., Poco, J., Paula, R. de, Nonato, L. G., & Gomez-Nieto, E. M. (2021). DRIFT: a visual analytic tool for scientific literature exploration based on textual and image content. In Proceedings. Los Alamitos: IEEE. doi:10.1109/SIBGRAPI54419.2021.00027
NLM
Pocco X, Poco J, Paula R de, Nonato LG, Gomez-Nieto EM. DRIFT: a visual analytic tool for scientific literature exploration based on textual and image content [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00027
Vancouver
Pocco X, Poco J, Paula R de, Nonato LG, Gomez-Nieto EM. DRIFT: a visual analytic tool for scientific literature exploration based on textual and image content [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/SIBGRAPI54419.2021.00027
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 title: 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: 12 ago. 2022.
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 2022 ago. 12 ] 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 2022 ago. 12 ] Available from: https://doi.org/10.1109/CBMS52027.2021.00059
Trabalho de evento
Comparison of value iteration, policy iteration and Q-Learning for solving decision-making problems (2021)
Hamadouche, Mohand ; Dezan, Catherine ; Espes, David ; Branco, Kalinka Regina Lucas Jaquie Castelo
Source: Proceedings. Conference title: International Conference on Unmanned Aircraft Systems - ICUAS. Unidade: ICMC
Subjects: TOMADA DE DECISÃO, APRENDIZADO COMPUTACIONAL, PROCESSOS DE MARKOV
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HAMADOUCHE, Mohand et al. Comparison of value iteration, policy iteration and Q-Learning for solving decision-making problems. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICUAS51884.2021.9476691. Acesso em: 12 ago. 2022.
APA
Hamadouche, M., Dezan, C., Espes, D., & Branco, K. R. L. J. C. (2021). Comparison of value iteration, policy iteration and Q-Learning for solving decision-making problems. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICUAS51884.2021.9476691
NLM
Hamadouche M, Dezan C, Espes D, Branco KRLJC. Comparison of value iteration, policy iteration and Q-Learning for solving decision-making problems [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICUAS51884.2021.9476691
Vancouver
Hamadouche M, Dezan C, Espes D, Branco KRLJC. Comparison of value iteration, policy iteration and Q-Learning for solving decision-making problems [Internet]. Proceedings. 2021 ;[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/ICUAS51884.2021.9476691
Artigo de periodico
Improving parallelism in Git and GNU: strategies, difficulties, and lessons learned (2021)
Bernardino, Matheus Tavares ; Belinassi, Giuliano; Meirelles, Paulo ; Guerra, Eduardo Martins ; Goldman, Alfredo
Source: IEEE Software. Unidade: IME
Subjects: PROGRAMAÇÃO PARALELA, SOFTWARE LIVRE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BERNARDINO, Matheus Tavares et al. Improving parallelism in Git and GNU: strategies, difficulties, and lessons learned. IEEE Software, v. 38, n. 5, p. 92-100, 2021Tradução . . Disponível em: https://doi.org/10.1109/MS.2020.3020932. Acesso em: 12 ago. 2022.
APA
Bernardino, M. T., Belinassi, G., Meirelles, P., Guerra, E. M., & Goldman, A. (2021). Improving parallelism in Git and GNU: strategies, difficulties, and lessons learned. IEEE Software, 38( 5), 92-100. doi:10.1109/MS.2020.3020932
NLM
Bernardino MT, Belinassi G, Meirelles P, Guerra EM, Goldman A. Improving parallelism in Git and GNU: strategies, difficulties, and lessons learned [Internet]. IEEE Software. 2021 ; 38( 5): 92-100.[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/MS.2020.3020932
Vancouver
Bernardino MT, Belinassi G, Meirelles P, Guerra EM, Goldman A. Improving parallelism in Git and GNU: strategies, difficulties, and lessons learned [Internet]. IEEE Software. 2021 ; 38( 5): 92-100.[citado 2022 ago. 12 ] Available from: https://doi.org/10.1109/MS.2020.3020932

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