Name
Title | ||
|---|---|---|
Obtaining Optimal Bio-PEPA Model Using Association Rules: Approach Applied to Tuberculosis Case Study. |
Abstract | ||
|---|---|---|
The computational modelling has been applied in several works, which exert considerable positive impact, particularly in epidemiological field. However, modelling epidemics is very sensitive where selecting appropriate feature and model structure is challenging task for experts and epidemiologists. To overcome this limitation, we presented in previous work a methodology combining computational modelling and decision tree techniques. The approach has been validated on tuberculosis case study. Therefore, as comparative study, we propose here to apply association rules algorithms. The results indicate the epidemiological relevance of the extracted rules. Thus, the enhanced Bio-PEPA model demonstrates the robustness of the proposed approach. |
Year | Venue | Field |
|---|---|---|
2016 | ISCRAM-med | Decision tree,Data mining,Computer science,Robustness (computer science),Association rule learning,PEPA |
DocType | Citations | PageRank |
Conference | 1 | 0.35 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dalila Hamami | 1 | 2 | 1.72 |
| Baghdad Atmani | 2 | 70 | 18.72 |