| Título: | Epidemiological data mining of cardiovascular Bayesian networks |
| Autores: |
Twardy, Charles R; Clayton School of Information Technology, Monash University Nicholson, Ann E; Clayton School of Information Technology, Monash University Korb, Kevin B; Clayton School of Information Technology, Monash University McNeil, John; Department of Epidemiology & Preventive Medicine, Monash University |
| Fecha: | 2006-03-22 |
| Publicador: | Electronic journal of health informatics |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Publication |
| Tema: |
Bayesian Networks; Artificial Intelligence, Epidemiology; Data Mining; Knowledge Engineering; Coronary Heart Disease Bayesian Networks; Artificial Intelligence, Epidemiology; Data Mining; Knowledge Engineering; Coronary Heart Disease |
| Descripción: | Although BNs have been used successfully for many medical diagnosis problems, there have been few applications to epidemiological data where data mining methods play a significant role. In this paper, we look at the application of BNs to epidemiological data, specifically assessment of risk for coronary heart disease (CHD). We build the BNs: (1) by knowledge engineering BNs from two epidemiological models of CHD in the literature; (2) by applying a causal BN learner. We evaluate these BNs using cross-validation. We compared performance in predicting CHD events over 10 years, measuring area under the ROC curve and Bayesian information reward. The knowledge engineered BNs performed as well as logistic regression, while being easier to interpret. These BNs will serve as the baseline in future efforts to extend BN technology to better handle epidemiological data, specifically to model CHD. |
| Idioma: | Inglés |
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