Expert system for predicting unstable angina based on Bayesian networks

Expert Systems with Applications

Volumn 40, Issue 12, 2013, Pages 5004-5010

  Vila Francés, Joan ^a   Sanchís, Juan ^b   Soria Olivas, Emilio ^a   JoséSerrano, Antonio ^a   Martínez Sober, Marcelino ^a   Bonanad, Clara ^b   Ventura, Silvia ^b  

^a UNIVERSITY OF VALENCIA   (Spain)

^b HOSPITAL CLÍNICO UNIVERSITARIO   (Spain)

Author keywords

Bayesian networks; Expert systems; Medical applications

Indexed keywords

DECISION SUPPORT SYSTEMS; EXPERT SYSTEMS; HEALTH RISKS; MEDICAL APPLICATIONS;

BAYESIAN NETWORK MODELS; CLINICAL DECISION SUPPORT; HEALTH RESOURCES; NETWORK MODELING; PREDICTIVE VALUES; WAITING LISTS; WEB APPLICATION;

BAYESIAN NETWORKS;

EID: 84885050499     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2013.03.029     Document Type: Article

References (12)

1. Steyerberg, E. (2009). Clinical prediction models:Apractical approach todevelopment, validation and updating. Springer.
2. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. (2011). Big data:The next frontier for innovation, competition, and productivity, Tech.rep., McKinsey Global Institute.
3. Escaned, J., Roig, E., Chorro, F., Teresa, E. D., Jiménez, M., deSá, E. L., et al. (2008). Ámbito deactuació ndelacardiología enlos nuevos escenarios clínicos. documento de consenso delasociedad espa nola decardiologí a. Revista Espa nola deCardiología, 61, 170-184.
4. Sanchis, J., Bodí, V., Bertomeu, V., Gómez, C., Consuegra, L., Bosch, M., et al. (2006). Usefulness of early exercise testing and clinical risk score for prognostic evaluation in chest pain units without preexisting evidence ofmyocardial ischemia. American Journal of Cardiology, 97, 633-635. (Pubitemid 43255029)
5. Alpaydin, E. (2009). Introduction to machine learning. MIT Press.
6. Lucas, P., Gaag, L., & Abu-Hanna, A. (2004). Bayesian networks inbiomedicine and health-care. Artificial Intelligence inMedicine, 30, 201-214.
7. Korb, K. B., & Nicholson, A. E. (2011). Bayesian artificial intelligence. CRC Press.
8. Koller, D., & Friedman, N. (2009). Probabilistic graphical models: Principles and techniques. MIT Press.
9. Rusell, S., & Norvig, P. (2009). Artificial intelligence:Amodern approach. Prentice Hall.
10. Murphy, K. (2007) TheBayes net toolbox for matlab. Computing Science and Statistics, 33. URL: .
11. Carletta, J. (1996). Assessing agreement onclassificationtasks:The kappa statistic. Computational Linguistics, 22(2), 249-254.
12. Fawcett, T. (2004). Roc graphs:Notes and practical considerations for researchers, Tech. rep., HPLaboratories.