Your browser doesn't support javascript.
loading
Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection.
Mamouei, Mohammad; Budidha, Karthik; Baishya, Nystha; Qassem, Meha; Kyriacou, Panayiotis.
Afiliación
  • Mamouei M; Research Centre for Biomedical Engineering, Department of Electrical and Electronic Engineering, School of Mathematics, Computer Science and Engineering, City, University of London, London, UK. Mohammad.mamouei@city.ac.uk.
  • Budidha K; Research Centre for Biomedical Engineering, Department of Electrical and Electronic Engineering, School of Mathematics, Computer Science and Engineering, City, University of London, London, UK.
  • Baishya N; Research Centre for Biomedical Engineering, Department of Electrical and Electronic Engineering, School of Mathematics, Computer Science and Engineering, City, University of London, London, UK.
  • Qassem M; Research Centre for Biomedical Engineering, Department of Electrical and Electronic Engineering, School of Mathematics, Computer Science and Engineering, City, University of London, London, UK.
  • Kyriacou P; Research Centre for Biomedical Engineering, Department of Electrical and Electronic Engineering, School of Mathematics, Computer Science and Engineering, City, University of London, London, UK.
Sci Rep ; 10(1): 16905, 2020 10 09.
Article en En | MEDLINE | ID: mdl-33037265
Asunto(s)
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Ácido Láctico Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2020 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Ácido Láctico Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Sci Rep Año: 2020 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: Reino Unido