Abstract
A medical diagnosis system (DRCAD), which consists of two sub-modules Bayesian and rule-based inference models, is presented in this study. Three types of tests are conducted to assess the performances of the models producing synthetic data based on the ALARM network. The results indicate that the linear combination of the aforementioned models leads to a 5% and a 30% improvement in medical diagnosis when compared to the "Rule Based Method" and the "Bayesian Network Based Method", respectively.
Original language | English |
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Pages (from-to) | 29-44 |
Number of pages | 16 |
Journal | International Journal of Computational Intelligence Systems |
Volume | 7 |
Issue number | SUPPL.1 |
DOIs | |
Publication status | Published - Jan 2014 |
Keywords
- ALARM Network
- Bayesian Networks
- Medical Decision Support Systems
- Rule-Based Systems