Decision Support based on Bio-PEPA Modeling and Decision Tree Induction
| Autor: | Atmani Baghdad, Dalila Hamami, Carron Shankland |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Matching (statistics) Decision support system Information Systems and Management Computer science Strategy and Management Decision tree 02 engineering and technology Management Science and Operations Research Machine learning computer.software_genre Management Information Systems 03 medical and health sciences 0202 electrical engineering electronic engineering information engineering Influence diagram Decision engineering business.industry Evidential reasoning approach Intelligent decision support system 030104 developmental biology 020201 artificial intelligence & image processing Artificial intelligence Data mining business computer Information Systems Decision analysis |
| Zdroj: | International Journal of Information Systems in the Service Sector. 9:71-101 |
| ISSN: | 1935-5696 1935-5688 |
| DOI: | 10.4018/ijisss.2017040104 |
| Popis: | The problem of selecting determinant features generating appropriate model structure is a challenge in epidemiological modelling. Disease spread is highly complex, and experts develop their understanding of its dynamic over years. There is an increasing variety and volume of epidemiological data which adds to the potential confusion. The authors propose here to make use of that data to better understand disease systems. Decision tree techniques have been extensively used to extract pertinent information and improve decision making. In this paper, the authors propose an innovative structured approach combining decision tree induction with Bio-PEPA computational modelling, and illustrate the approach through application to tuberculosis. By using decision tree induction, the enhanced Bio-PEPA model shows considerable improvement over the initial model with regard to the simulated results matching observed data. The key finding is that the developer expresses a realistic predictive model using relevant features, thus considering this approach as decision support, empowers the epidemiologist in his policy decision making. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|