Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Maicon Herverton Lino Ferreira da Silva Barros"'
Autor:
Maicon Herverton Lino Ferreira da Silva Barros, Guto Leoni Santos, Maria Gabriela de Almeida Rodrigues, Vanderson Sampaio, Theo Lynn, Patricia Takako Endo
Publikováno v:
Scientific Data, Vol 9, Iss 1, Pp 1-8 (2022)
Abstract After COVID-19, tuberculosis (TB) is the leading cause of death by an infectious disease in the world. This work presents a data set based on data collected from the Brazilian Information System for Notifiable Diseases (SINAN) for the period
Externí odkaz:
https://doaj.org/article/b722c76de41f432b8551e5112b27aa84
Autor:
Maicon Herverton Lino Ferreira da Silva Barros, Geovanne Oliveira Alves, Lubnnia Morais Florêncio Souza, Elisson da Silva Rocha, João Fausto Lorenzato de Oliveira, Theo Lynn, Vanderson Sampaio, Patricia Takako Endo
Publikováno v:
Informatics, Vol 8, Iss 2, p 27 (2021)
Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed w
Externí odkaz:
https://doaj.org/article/8a358e90567e498886c5703afa5ca90f
Autor:
Maicon Herverton Lino Ferreira da Silva Barros, Flávio Secco Fonseca, Marcos André Santos Galindo, Arianne Sarmento Torcate
Publikováno v:
Revista de Engenharia e Pesquisa Aplicada. 6:1-11
O aumento significativo de infrações de trânsito tem se tornado algo casual na vida dos brasileiros. A cidade do Recife, estado de Pernambuco, segundo a empresa Holandesa TomTom Traffic, no ano de 2018, ocupava a 10º posição entre as cidades co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdd7b24571e69da50b8e21d1c9358b4e
https://doi.org/10.25286/repa.v6i3.1679
https://doi.org/10.25286/repa.v6i3.1679
Autor:
Lubnnia Morais Florêncio Souza, Vanderson de Souza Sampaio, Patricia Takako Endo, Geovanne Oliveira Alves, Maicon Herverton Lino Ferreira da Silva Barros, Elisson Rocha, João Fausto Lorenzato de Oliveira, Theo Lynn
Publikováno v:
da Silva Barros, Maicon Herverton Lino Ferreira ORCID: 0000-0002-0275-3298 , Alves, Geovanne Oliveira ORCID: 0000-0002-2084-5516 , Souza, Lubnnia Morais Florêncio ORCID: 0000-0002-2188-6272 , da Silva Rocha, Elisson ORCID: 0000-0002-7742-2995 , Oliveira, João Fausto Lorenzato de ORCID: 0000-0002-1150-4904 , Lynn, Theo ORCID: 0000-0001-9284-7580 , Sampaio, Vanderson ORCID: 0000-0001-7307-8851 and Takako Endo, Patricia ORCID: 0000-0002-9163-5583 (2021) Benchmarking machine learning models to assist in the prognosis of tuberculosis. Informatics, 8 (2). ISSN 2227-9709
Informatics, Vol 8, Iss 27, p 27 (2021)
Informatics
Volume 8
Issue 2
Informatics, Vol 8, Iss 27, p 27 (2021)
Informatics
Volume 8
Issue 2
Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa86013aa04ccc488d9c71f5901ff943
http://doras.dcu.ie/27522/
http://doras.dcu.ie/27522/
Autor:
Elisson Rocha, João Fausto Lorenzato de Oliveira, Geovanne Oliveira Alves, Lubnnia Morais Florêncio Souza, Vanderson de Souza Sampaio, Patricia Takako Endo, Theo Lynn, Maicon Herverton Lino Ferreira da Silva Barros
Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d12da423dd953e92c27a2f5835996a9b
https://doi.org/10.20944/preprints202103.0284.v2
https://doi.org/10.20944/preprints202103.0284.v2
Autor:
Maicon Herverton Lino Ferreira da Silva Barros, Patricia Takako Endo, Vanderson de Souza Sampaio, Morgana Thalita da Silva Leite, Theo Lynn
Publikováno v:
CyberSA
The volume of data generated by health systems is substantial and is likely to continue growing exponentially with the growing adoption of the Internet of Things. Efforts to improve data discovery and integration are complicated by the complexity, di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2250bbb3ab02086c2816d1b9344b535
https://doi.org/10.1109/cybersa49311.2020.9139699
https://doi.org/10.1109/cybersa49311.2020.9139699