A drug administration decision support system

Details

Serval ID
serval:BIB_1166702CE584
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
A drug administration decision support system
Title of the conference
2012 Workshop on Pharmaco-Informatics for Drug Discovery in Conjunction with 2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2012)
Author(s)
You W., Simalatsar A., Widmer N., De Micheli G.
Address
Philadelphia, Pennsylvania, United-States, October 4-7, 2012
ISBN
978-1-4673-2744-2
Publication state
Published
Issued date
2012
Peer-reviewed
Oui
Pages
122-129
Language
english
Abstract
Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.
Keywords
Decision Support System, RANSAC algorithm, Support Vector Machine
Create date
26/12/2012 18:42
Last modification date
20/08/2019 12:39
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