Your browser doesn't support javascript.
loading
Multi-resistant diarrheagenic Escherichia coli identified by FTIR and machine learning: a feasible strategy to improve the group classification.
Marangoni-Ghoreyshi, Yasmin Garcia; Franca, Thiago; Esteves, José; Maranni, Ana; Pereira Portes, Karine Dorneles; Cena, Cicero; Leal, Cassia R B.
Affiliation
  • Marangoni-Ghoreyshi YG; UFMS - Universidade Federal de Mato Grosso do Sul, Graduate Program in Veterinary Science (CIVET) Campo Grande MS Brazil.
  • Franca T; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br.
  • Esteves J; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br.
  • Maranni A; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br.
  • Pereira Portes KD; UFMS - Universidade Federal de Mato Grosso do Sul, Animal Science Undergraduate, PIBIT/CNPq Campo Grande MS Brazil.
  • Cena C; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br.
  • Leal CRB; UFMS - Universidade Federal de Mato Grosso do Sul, Graduate Program in Veterinary Science (CIVET) Campo Grande MS Brazil.
RSC Adv ; 13(36): 24909-24917, 2023 Aug 21.
Article in En | MEDLINE | ID: mdl-37608796
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: RSC Adv Year: 2023 Document type: Article
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: RSC Adv Year: 2023 Document type: Article