2026-04-19T16:38:34Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/85722024-02-06T01:05:24Zcom_10259_3847com_10259_5086com_10259_2604col_10259_7109col_10259_7409
Repositorio Institucional de la Universidad de Burgos
author
Curiel Herrera, Leticia Elena
author
Baruque Zanón, Bruno
author
Dueñas, Carlos
author
Corchado, Emilio
author
Pérez-Tárrago, Cristina
2024-02-05T08:13:13Z
2024-02-05T08:13:13Z
2011
978-3-642-23878-9
http://hdl.handle.net/10259/8572
10.1007/978-3-642-23878-9_54
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.
eng
Genetic algorithms
Support vector machine
Infective endocarditis
Feature selection algorithm
Imperialist competitive algorithm
Genetic Algorithms to Simplify Prognosis of Endocarditis
info:eu-repo/semantics/bookPart
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URL
https://riubu.ubu.es/bitstream/10259/8572/1/Curiel-Genetic_algorithms_to_simplify_prognosis_of_endocarditis.pdf
File
MD5
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192180
application/pdf
Curiel-Genetic_algorithms_to_simplify_prognosis_of_endocarditis.pdf