Improving Downs Syndrome Prediction with a Smart Medical Data Classification Model- Case of Study

In health areas like drugs application, surgeries, projection of the spreading of contagious diseases, study of cancer and others, estimation, accuracy and precision are crucial. In the last few years, machine-learning methods have been used to obtain the best precision in prediction and classificat...

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Auteur principal:	Saldana-Barrios, Juan Jose (author)
Autres auteurs:	Concepción, Tomas (author), Vargas-Lombardo, Miguel (author)
Format:	article
Langue:	espagnol
Publié:	2016
Sujets:	Naïve Bayes, Machine Learning, Support Vector Machine, Down’s syndrome, eHealth Clasificador Bayesiano Ingenuo, Máquina de Aprendizaje Automático, Máquina de Vectores de Soporte, Síndrome de Down, Salud Electrónica.
Accès en ligne:	http://revistas.utp.ac.pa/index.php/id-tecnologico/article/view/1234 http://ridda2.utp.ac.pa/handle/123456789/1814
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