Example-based support vector machine for drug concentration analysis

Détails

ID Serval
serval:BIB_9B320455D51E
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Titre
Example-based support vector machine for drug concentration analysis
Titre de la conférence
EMBC 2011, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Auteur(s)
You W., Widmer N., De Micheli G.
Adresse
Boston, Massachusetts, United-States, August 30-September 3, 2011
ISBN
1557-170X (Print)
ISSN-L
1557-170X
Statut éditorial
Publié
Date de publication
2011
Peer-reviewed
Oui
Volume
2011
Série
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011)
Pages
153-157
Langue
anglais
Résumé
Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.
Pubmed
Création de la notice
20/01/2012 22:58
Dernière modification de la notice
20/08/2019 15:02
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