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BIBTEX RIS

Genetic Algorithms to Simplify Prognosis of Endocarditis

2011; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-23878-9_54

ISSN

1611-3349

Autores

Leticia Curiel, Bruno Baruque, Carlos Dueñas, Emilio Corchado, Cristina Pérez-Tárrago,

Tópico(s)

Advanced Statistical Process Monitoring

Resumo

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.

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