ReP USP - Resultado da busca

Artigo de periodico
Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging (2020)
Faleiros, Matheus Calil; Nogueira-Barbosa, Marcello Henrique ; Dalto, Vitor Faeda ; Júnior, José Raniery Ferreira ; Tenório, Ariane Priscilla Magalhães; Luppino-Assad, Rodrigo; Louzada Júnior, Paulo ; Rangayyan, Rangaraj Mandayam; Azevedo-Marques, Paulo Mazzoncini de
Source: Advances in Rheumatology. Unidade: FMRP
Subjects: DIAGNÓSTICO POR COMPUTADOR, ARTICULAÇÕES, DOENÇAS REUMÁTICAS, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FALEIROS, Matheus Calil et al. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. Advances in Rheumatology, v. 60, p. 1-10, 2020Tradução . . Disponível em: https://doi.org/10.1186/s42358-020-00126-8. Acesso em: 25 set. 2024.
APA
Faleiros, M. C., Nogueira-Barbosa, M. H., Dalto, V. F., Júnior, J. R. F., Tenório, A. P. M., Luppino-Assad, R., et al. (2020). Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging. Advances in Rheumatology, 60, 1-10. doi:10.1186/s42358-020-00126-8
NLM
Faleiros MC, Nogueira-Barbosa MH, Dalto VF, Júnior JRF, Tenório APM, Luppino-Assad R, Louzada Júnior P, Rangayyan RM, Azevedo-Marques PM de. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging [Internet]. Advances in Rheumatology. 2020 ; 60 1-10.[citado 2024 set. 25 ] Available from: https://doi.org/10.1186/s42358-020-00126-8
Vancouver
Faleiros MC, Nogueira-Barbosa MH, Dalto VF, Júnior JRF, Tenório APM, Luppino-Assad R, Louzada Júnior P, Rangayyan RM, Azevedo-Marques PM de. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging [Internet]. Advances in Rheumatology. 2020 ; 60 1-10.[citado 2024 set. 25 ] Available from: https://doi.org/10.1186/s42358-020-00126-8
Artigo de periodico
Identifying frailty levels and associated factors in a population living in the context of poverty and social vulnerability (2017)
Zazzetta, M. S; Gomes, G. A. O; Orlandi, F. S; Gratão, A. C. M; Vasilceac, F. A; Gramani-Say, K; Ponti, Moacir Antonelli ; Castro, P. C; Pavarini, S. C. I; Menezes, A. L. C; Nascimento, C. M. C; Cominetti, M. R
Source: Journal of Frailty & Aging. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, IDOSOS, VULNERABILIDADE, POBREZA, SÃO CARLOS (SP)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ZAZZETTA, M. S et al. Identifying frailty levels and associated factors in a population living in the context of poverty and social vulnerability. Journal of Frailty & Aging, v. 6, n. 1, p. 29-32, 2017Tradução . . Disponível em: https://doi.org/10.14283/jfa.2016.116. Acesso em: 25 set. 2024.
APA
Zazzetta, M. S., Gomes, G. A. O., Orlandi, F. S., Gratão, A. C. M., Vasilceac, F. A., Gramani-Say, K., et al. (2017). Identifying frailty levels and associated factors in a population living in the context of poverty and social vulnerability. Journal of Frailty & Aging, 6( 1), 29-32. doi:10.14283/jfa.2016.116
NLM
Zazzetta MS, Gomes GAO, Orlandi FS, Gratão ACM, Vasilceac FA, Gramani-Say K, Ponti MA, Castro PC, Pavarini SCI, Menezes ALC, Nascimento CMC, Cominetti MR. Identifying frailty levels and associated factors in a population living in the context of poverty and social vulnerability [Internet]. Journal of Frailty & Aging. 2017 ; 6( 1): 29-32.[citado 2024 set. 25 ] Available from: https://doi.org/10.14283/jfa.2016.116
Vancouver
Zazzetta MS, Gomes GAO, Orlandi FS, Gratão ACM, Vasilceac FA, Gramani-Say K, Ponti MA, Castro PC, Pavarini SCI, Menezes ALC, Nascimento CMC, Cominetti MR. Identifying frailty levels and associated factors in a population living in the context of poverty and social vulnerability [Internet]. Journal of Frailty & Aging. 2017 ; 6( 1): 29-32.[citado 2024 set. 25 ] Available from: https://doi.org/10.14283/jfa.2016.116
Artigo de periodico
Similarity measures for comparing biclusterings (2014)
Horta, Danilo; Campello, Ricardo José Gabrielli Barreto
Source: IEEE/ACM Transactions on Computational Biology and Bioinformatics. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
HORTA, Danilo e CAMPELLO, Ricardo José Gabrielli Barreto. Similarity measures for comparing biclusterings. IEEE/ACM Transactions on Computational Biology and Bioinformatics, v. 11, n. 5, p. 942-954, 2014Tradução . . Disponível em: https://doi.org/10.1109/TCBB.2014.2325016. Acesso em: 25 set. 2024.
APA
Horta, D., & Campello, R. J. G. B. (2014). Similarity measures for comparing biclusterings. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11( 5), 942-954. doi:10.1109/TCBB.2014.2325016
NLM
Horta D, Campello RJGB. Similarity measures for comparing biclusterings [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2014 ; 11( 5): 942-954.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TCBB.2014.2325016
Vancouver
Horta D, Campello RJGB. Similarity measures for comparing biclusterings [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2014 ; 11( 5): 942-954.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TCBB.2014.2325016
Artigo de periodico
Proximity measures for clustering gene expression microarray data: a validation methodology and a comparative analysis (2013)
Jaskowiak, Pablo A; Campello, Ricardo José Gabrielli Barreto; Costa, Ivan G
Source: IEEE/ACM Transactions on Computational Biology and Bioinformatics. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
JASKOWIAK, Pablo A e CAMPELLO, Ricardo José Gabrielli Barreto e COSTA, Ivan G. Proximity measures for clustering gene expression microarray data: a validation methodology and a comparative analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, v. 10, n. 4, p. 845-857, 2013Tradução . . Disponível em: https://doi.org/10.1109/TCBB.2013.9. Acesso em: 25 set. 2024.
APA
Jaskowiak, P. A., Campello, R. J. G. B., & Costa, I. G. (2013). Proximity measures for clustering gene expression microarray data: a validation methodology and a comparative analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10( 4), 845-857. doi:10.1109/TCBB.2013.9
NLM
Jaskowiak PA, Campello RJGB, Costa IG. Proximity measures for clustering gene expression microarray data: a validation methodology and a comparative analysis [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2013 ; 10( 4): 845-857.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TCBB.2013.9
Vancouver
Jaskowiak PA, Campello RJGB, Costa IG. Proximity measures for clustering gene expression microarray data: a validation methodology and a comparative analysis [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2013 ; 10( 4): 845-857.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TCBB.2013.9
Artigo de periodico
Gating-signal propagation by a feed-forward neural motif (2013)
Liang, Xiaoming; Yanchuk, Serhiy; Liang, Zhao
Source: Physical Review E. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL, SISTEMAS DINÂMICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIANG, Xiaoming e YANCHUK, Serhiy e LIANG, Zhao. Gating-signal propagation by a feed-forward neural motif. Physical Review E, v. 88, n. 1, p. 012910-1-012910-7, 2013Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.88.012910. Acesso em: 25 set. 2024.
APA
Liang, X., Yanchuk, S., & Liang, Z. (2013). Gating-signal propagation by a feed-forward neural motif. Physical Review E, 88( 1), 012910-1-012910-7. doi:10.1103/PhysRevE.88.012910
NLM
Liang X, Yanchuk S, Liang Z. Gating-signal propagation by a feed-forward neural motif [Internet]. Physical Review E. 2013 ; 88( 1): 012910-1-012910-7.[citado 2024 set. 25 ] Available from: https://doi.org/10.1103/PhysRevE.88.012910
Vancouver
Liang X, Yanchuk S, Liang Z. Gating-signal propagation by a feed-forward neural motif [Internet]. Physical Review E. 2013 ; 88( 1): 012910-1-012910-7.[citado 2024 set. 25 ] Available from: https://doi.org/10.1103/PhysRevE.88.012910
Artigo de periodico
Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions (2013)
Machado, Jeremias B; Campello, Ricardo José Gabrielli Barreto; Amaral, Wagner Caradori
Source: IEEE Transactions on Cybernetics. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MACHADO, Jeremias B e CAMPELLO, Ricardo José Gabrielli Barreto e AMARAL, Wagner Caradori. Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions. IEEE Transactions on Cybernetics, v. 43, n. ju 2013, p. 858-870, 2013Tradução . . Disponível em: https://doi.org/10.1109/TSMCB.2012.2217323. Acesso em: 25 set. 2024.
APA
Machado, J. B., Campello, R. J. G. B., & Amaral, W. C. (2013). Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions. IEEE Transactions on Cybernetics, 43( ju 2013), 858-870. doi:10.1109/TSMCB.2012.2217323
NLM
Machado JB, Campello RJGB, Amaral WC. Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions [Internet]. IEEE Transactions on Cybernetics. 2013 ; 43( ju 2013): 858-870.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TSMCB.2012.2217323
Vancouver
Machado JB, Campello RJGB, Amaral WC. Takagi-Sugeno fuzzy models in the framework of orthonormal basis functions [Internet]. IEEE Transactions on Cybernetics. 2013 ; 43( ju 2013): 858-870.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TSMCB.2012.2217323
Artigo de periodico
A simpler and more accurate AUTO-HDS framework for clustering and visualization of biological data (2012)
Campello, Ricardo José Gabrielli Barreto; Moulavi, Davoud; Sander, Joerg
Source: IEEE/ACM Transactions on Computational Biology and Bioinformatics. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAMPELLO, Ricardo José Gabrielli Barreto e MOULAVI, Davoud e SANDER, Joerg. A simpler and more accurate AUTO-HDS framework for clustering and visualization of biological data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, v. no/dez. 2012, n. 6, p. 1850-1852, 2012Tradução . . Disponível em: https://doi.org/10.1109/TCBB.2012.115. Acesso em: 25 set. 2024.
APA
Campello, R. J. G. B., Moulavi, D., & Sander, J. (2012). A simpler and more accurate AUTO-HDS framework for clustering and visualization of biological data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, no/dez. 2012( 6), 1850-1852. doi:10.1109/TCBB.2012.115
NLM
Campello RJGB, Moulavi D, Sander J. A simpler and more accurate AUTO-HDS framework for clustering and visualization of biological data [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2012 ; no/dez. 2012( 6): 1850-1852.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TCBB.2012.115
Vancouver
Campello RJGB, Moulavi D, Sander J. A simpler and more accurate AUTO-HDS framework for clustering and visualization of biological data [Internet]. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2012 ; no/dez. 2012( 6): 1850-1852.[citado 2024 set. 25 ] Available from: https://doi.org/10.1109/TCBB.2012.115
Artigo de periodico
Phase-noise-induced resonance in a single neuronal system (2011)
Liang, Xiaoming; Liang, Zhao; Liu, Zonghua
Source: Physical Review E. Unidade: ICMC
Subjects: COMPUTAÇÃO GRÁFICA, PROCESSAMENTO DE IMAGENS, INTELIGÊNCIA ARTIFICIAL, SISTEMAS DINÂMICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LIANG, Xiaoming e LIANG, Zhao e LIU, Zonghua. Phase-noise-induced resonance in a single neuronal system. Physical Review E, v. 84, n. 3, p. 031916-1-031916-5, 2011Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.84.031916. Acesso em: 25 set. 2024.
APA
Liang, X., Liang, Z., & Liu, Z. (2011). Phase-noise-induced resonance in a single neuronal system. Physical Review E, 84( 3), 031916-1-031916-5. doi:10.1103/PhysRevE.84.031916
NLM
Liang X, Liang Z, Liu Z. Phase-noise-induced resonance in a single neuronal system [Internet]. Physical Review E. 2011 ; 84( 3): 031916-1-031916-5.[citado 2024 set. 25 ] Available from: https://doi.org/10.1103/PhysRevE.84.031916
Vancouver
Liang X, Liang Z, Liu Z. Phase-noise-induced resonance in a single neuronal system [Internet]. Physical Review E. 2011 ; 84( 3): 031916-1-031916-5.[citado 2024 set. 25 ] Available from: https://doi.org/10.1103/PhysRevE.84.031916
Trabalho de evento-resumo periodico
Machine learning system investigation in pharmaceutical development (1999)
Nicoletti, Maria Aparecida ; Nicoletti, Maria do Carmo; Magalhães, João Fernandes
Source: Bollettino Chimico Farmaceutico. Conference titles: Congress of Pharmaceutical Sciences. Unidade: FCF
Subjects: FARMACOLOGIA, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NICOLETTI, Maria Aparecida e NICOLETTI, Maria do Carmo e MAGALHÃES, João Fernandes. Machine learning system investigation in pharmaceutical development. Bollettino Chimico Farmaceutico. Milano: Società Editoriale Farmaceutica. . Acesso em: 25 set. 2024. , 1999
APA
Nicoletti, M. A., Nicoletti, M. do C., & Magalhães, J. F. (1999). Machine learning system investigation in pharmaceutical development. Bollettino Chimico Farmaceutico. Milano: Società Editoriale Farmaceutica.
NLM
Nicoletti MA, Nicoletti M do C, Magalhães JF. Machine learning system investigation in pharmaceutical development. Bollettino Chimico Farmaceutico. 1999 ; 138( 2): 26.[citado 2024 set. 25 ]
Vancouver
Nicoletti MA, Nicoletti M do C, Magalhães JF. Machine learning system investigation in pharmaceutical development. Bollettino Chimico Farmaceutico. 1999 ; 138( 2): 26.[citado 2024 set. 25 ]
Trabalho de evento-resumo periodico
Teaching a neural net to predict the length of stay in an intensive care unit (1999)
Lavrador, Marco Aurélio Sicchiroli
Source: Bollettino Chimico Farmaceutico. Conference titles: Congress of Pharmaceutical Sciences. Unidade: FCFRP
Subjects: MEDICINA, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LAVRADOR, Marco Aurélio Sicchiroli. Teaching a neural net to predict the length of stay in an intensive care unit. Bollettino Chimico Farmaceutico. Milano: Societá Editoriale Farmaceutica. . Acesso em: 25 set. 2024. , 1999
APA
Lavrador, M. A. S. (1999). Teaching a neural net to predict the length of stay in an intensive care unit. Bollettino Chimico Farmaceutico. Milano: Societá Editoriale Farmaceutica.
NLM
Lavrador MAS. Teaching a neural net to predict the length of stay in an intensive care unit. Bollettino Chimico Farmaceutico. 1999 ; 132( 2): CCLXV.[citado 2024 set. 25 ]
Vancouver
Lavrador MAS. Teaching a neural net to predict the length of stay in an intensive care unit. Bollettino Chimico Farmaceutico. 1999 ; 132( 2): CCLXV.[citado 2024 set. 25 ]

USP Schools

ReP

Filtros

Authors

USP affiliated authors

Date published

Subjects

Source title

Indexado em

Normalized affiliation

Non normalized affiliation