RT info:eu-repo/semantics/article
T1 Using machine learning for improving knowledge on antibacterial effect of bioactive glass
A1 Echezarreta López, María Magdalena
A1 Landin, M.
A2 Ingeniería Química y Tecnología Farmacéutica
K1 Bioactive glass
K1 Antibacterial behaviour
K1 Modelling
K1 Artificial intelligence
K1 Neurofuzzy logic
K1 Machine learning
AB The aim of this work was to find relationships between critical bioactive glass characteristics and their antibacterial behaviour using an artificial intelligence tool. A large dataset including ingredients and process variables of the bioactive glasses production, bacterial characteristics and microbiological experimental conditions was generated from literature and analyzed by neurofuzzy logic technology. Our findings allow an explanation on the variability in antibacterial behaviour found by different authors and to obtain general conclusions about critical parameters of bioactive glasses to be considered in order to achieve activity against some of the most common skin and implant surgery pathogens.
YR 2013
FD 2013
LK http://riull.ull.es/xmlui/handle/915/37313
UL http://riull.ull.es/xmlui/handle/915/37313
LA en
NO Inteligencia artificial
NO financiado por POCTEP 0330IBEROMARE1P project, FEDER. ML (PR2010-0460)
DS Repositorio institucional de la Universidad de La Laguna
RD 01-sep-2024