Alexandros Rigas

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OBJECTIVES In this study a new method for asthma outcome prediction, which is based on Principal Component Analysis and Least Square Support Vector Machine Classifier, is presented. Most of the asthma cases appear during the first years of life. Thus, the early identification of young children being at high risk of developing persistent symptoms of the(More)
The prediction of asthma that persists throughout childhood and into adulthood, in early life of a child has practical, clinical and prognostic implications and sets the basis for the future prevention. Artificial Neural Networks (ANNs) seems to be a superior tool for analyzing data sets where nonlinear relationships are existing between the input data and(More)
Genetic Algorithms in combination with Artificial Neural Networks have been used to solve optimization problems in several domains. In this paper, an evolutionary algorithm consisting of an Artificial Neural Network and a Genetic Algorithm is presented for predicting the asthma outcome in children under the age of five. The most cases of asthma begin during(More)
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