RT info:eu-repo/semantics/bookPart
T1 Genetic Algorithms to Simplify Prognosis of Endocarditis
A1 Curiel Herrera, Leticia Elena
A1 Baruque Zanón, Bruno
A1 Dueñas, Carlos
A1 Corchado, Emilio
A1 Pérez-Tárrago, Cristina
K1 Genetic algorithms
K1 Support vector machine
K1 Infective endocarditis
K1 Feature selection algorithm
K1 Imperialist competitive algorithm
K1 Informática
K1 Computer science
K1 Medicina
K1 Medicine
AB This ongoing interdisciplinary research is based on the application of genetic algorithms to simplify the process of predicting the mortality of a critical illness called endocarditis. The goal is to determine the most relevant features (symptoms) of patients (samples) observed by doctors to predict the possible mortality once the patient is in treatment of bacterial endocarditis. This can help doctors to prognose the illness in early stages; by helping them to identify in advance possible solutions in order to aid the patient recover faster. The results obtained using a real data set, show that using only the features selected by employing a genetic algorithm from each patient’s case can predict with a quite high accuracy the most probable evolution of the patient.
PB Springer
SN 978-3-642-23878-9
YR 2011
FD 2011
LK http://hdl.handle.net/10259/8572
UL http://hdl.handle.net/10259/8572
LA eng
NO Trabajo presentado en: 12th International Conference, Norwich, UK, September 7-9, 2011. Proceedings
NO We would like to extend our thanks to Complejo Hospitalario Asistencial Universitario de Burgos (SACYL). This research has been partially supported through projects TIN2010-21272-C02-01 from the Spanish Ministry of Science and Innovation and Grupo Antolin Ingenieria, S.A., within the framework of project MAGNO2008 - 1028.- CENIT.
DS Repositorio Institucional de la Universidad de Burgos
RD 10-may-2024