Abstract
This paper presents a concept for a Decision Support System for Therapy Planning based on the Q-Learning method. It focuses the consideration on a multilevel approach for constructing a data driven evidence based system for classification of different drug dosages and their effectiveness for clinical trials. We consider time - ordered sequences of patient data called patient trials consisting of state, time and medication ordered by clinicians. A patient state generalization function to provide generalized patient states as categories of patient data is presented. For classification of medications we introduce a medication generalization function based on similarity classes of medications and a similarity function between two drug dosages. Both generalization functions are used for generalizing patient trials and for the synthesis of the Q-Learning agent for the Decision Support System.
| Originalsprache | Englisch |
|---|---|
| Titel | Proceedings of 21st European Modeling and Simulation Symposium EMSS 2009 |
| Herausgeber (Verlag) | DIPTEM University of Genova |
| Seiten | 1-6 |
| Publikationsstatus | Veröffentlicht - 2009 |
| Veranstaltung | 21st European Modeling and Simulation Symposium 2009 EMSS09 - Tenerife, Spanien Dauer: 23 Sep. 2009 → 25 Sep. 2009 http://www.msc-les.org/conf/emss2009/ |
Konferenz
| Konferenz | 21st European Modeling and Simulation Symposium 2009 EMSS09 |
|---|---|
| Land/Gebiet | Spanien |
| Ort | Tenerife |
| Zeitraum | 23.09.2009 → 25.09.2009 |
| Internetadresse |
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