Personalized drug administrations using Support Vector Machine

Détails

ID Serval
serval:BIB_F6FA8F70D5B4
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Personalized drug administrations using Support Vector Machine
Périodique
BioNanoScience
Auteur(s)
You W., Simalatsar A., Widmer N., De Micheli G.
ISSN
2191-1630 (Print)
2191-1649 (Electronic)
Statut éditorial
Publié
Date de publication
2013
Peer-reviewed
Oui
Volume
3
Numéro
4
Pages
378-393
Langue
anglais
Résumé
The decision-making process regarding drug dose, regularly used in everyday medical practice, is critical to patients' health and recovery. It is a challenging process, especially for a drug with narrow therapeutic ranges, in which a medical doctor decides the quantity (dose amount) and frequency (dose interval) on the basis of a set of available patient features and doctor's clinical experience (a priori adaptation). Computer support in drug dose administration makes the prescription procedure faster, more accurate, objective, and less expensive, with a tendency to reduce the number of invasive procedures. This paper presents an advanced integrated Drug Administration Decision Support System (DADSS) to help clinicians/patients with the dose computing. Based on a support vector machine (SVM) algorithm, enhanced with the random sample consensus technique, this system is able to predict the drug concentration values and computes the ideal dose amount and dose interval for a new patient. With an extension to combine the SVM method and the explicit analytical model, the advanced integrated DADSS system is able to compute drug concentration-to-time curves for a patient under different conditions. A feedback loop is enabled to update the curve with a new measured concentration value to make it more personalized (a posteriori adaptation).
Mots-clé
Drug dose computation, Support vector machine, Decision support system
Création de la notice
07/10/2013 16:02
Dernière modification de la notice
20/08/2019 16:23
Données d'usage