Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Julio Cesar Nievola"'
Autor:
Rafael Saraiva de Andrade Rodrigues, Eduardo Ferreira José Heise, Luis Felipe Hartmann, Guilherme Eduardo Rocha, Marcia Olandoski, Mariane Martins de Araújo Stefani, Ana Carla Pereira Latini, Cleverson Teixeira Soares, Andrea Belone, Patrícia Sammarco Rosa, Maria Araci de Andrade Pontes, Heitor de Sá Gonçalves, Rossilene Cruz, Maria Lúcia Fernandes Penna, Deborah Ribeiro Carvalho, Vinicius Medeiros Fava, Samira Bührer-Sékula, Gerson Oliveira Penna, Claudia Maria Cabral Moro, Julio Cesar Nievola, Marcelo Távora Mira
Publikováno v:
Frontiers in Medicine, Vol 10 (2023)
IntroductionLeprosy reactions (LR) are severe episodes of intense activation of the host inflammatory response of uncertain etiology, today the leading cause of permanent nerve damage in leprosy patients. Several genetic and non-genetic risk factors
Externí odkaz:
https://doaj.org/article/b26ff41f1e204a50b26f0dc2d27de53e
Autor:
Rossana Cristina Xavier Ferreira Vianna, Claudia Maria Cabral de Barra Moro, Samuel Jorge Moysés, Deborah Carvalho, Julio Cesar Nievola
Publikováno v:
Cadernos de Saúde Pública, Vol 26, Iss 3, Pp 535-542 (2010)
O estudo busca identificar padrões de características materno-fetais na predição da mortalidade infantil, por meio da incorporação de técnicas inovadoras, como a Mineração de Dados, que se mostram relevantes em Saúde Pública. Foi elaborada
Externí odkaz:
https://doaj.org/article/4286bf40c1684ac7b3526615b971d51f
Publikováno v:
Artificial Intelligence Review. 55:3243-3282
The classification task usually works with flat and batch learners, assuming problems as stationary and without relations between class labels. Nevertheless, several real-world problems do not assume these premises, i.e., data have labels organized h
Publikováno v:
2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
Publikováno v:
2022 International Joint Conference on Neural Networks (IJCNN).
Autor:
Karina Borges Mendes, Diego Paolo Tsutsumi, Bruno Samways dos Santos, Maria Teresinha Arns Steiner, Amanda Trojan Fenerich, Julio Cesar Nievola
Publikováno v:
IEEE Latin America Transactions. 18:59-66
The aim of this paper is to classify several types of headaches from patients, using different data analysis methods, with the application of two classifying algorithms, comparatively: Bayesian Networks (BN) and Artificial Neural Networks (ANN). The
Autor:
Rafael Saraiva de Andrade Rodrigues, Eduardo Ferreira José Heise, Luis Felipe Hartmann, Guilherme Eduardo Rocha, Marcia Olandoski, Mariane Martins de Araújo Stefani, Ana Carla Pereira Latini, Cleverson Teixeira Soares, Andrea Belone, Patrícia Sammarco Rosa, Maria Araci de Andrade Pontes, Heitor de Sá Gonçalves, Rossilene Cruz, Maria Lúcia Fernandes Penna, Deborah Ribeiro Carvalho, Vinicius Medeiros Fava, Samira Bührer-Sékula, Gerson Oliveira Penna, Claudia Maria Cabral Moro, Julio Cesar Nievola, Marcelo Távora Mira
Background: Leprosy reactions (LR) are severe episodes of intense activation of the host inflammatory response, of uncertain etiology, today the leading cause of permanent nerve damage in leprosy patients. Several genetic and non-genetic risk factors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78cf936449e859332586d5d60538c54a
https://doi.org/10.21203/rs.3.rs-1135008/v1
https://doi.org/10.21203/rs.3.rs-1135008/v1
Publikováno v:
2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
Autor:
Joielan Xipaia dos Santos, Julio Cesar Nievola, Jaime Wojciechowski, Deivison Venicio Souza, Alexandre Leão Gonçalves, Ana Paula Dalla Corte, Carlos Roberto Sanquetta
Publikováno v:
Journal of Sustainable Forestry. 38:755-768
Models constructed from machine learning are a potential non-parametric alternative for the prediction of biometric variables in opposition to traditional regression modeling. The hypothesis of thi...
Publikováno v:
Intelligent Systems ISBN: 9783030917012
Hierarchical data stream classification inherits the properties and constraints of hierarchical classification and data stream classification concomitantly. Therefore, it requires novel approaches that (i) can handle class hierarchies, (ii) can be up
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fa43d4cdbcea1e65456f5afef07ca69
https://doi.org/10.1007/978-3-030-91702-9_28
https://doi.org/10.1007/978-3-030-91702-9_28