title: Fusion of risk assessment models with application to coronary artery disease patients.
abstract: Several risk score models are available in literature to predict death/myocardial infarction event for coronary artery disease (CAD) patients, within a short period of time. However, the choice of the most adequate model is not straightforward since there might not be a consensus about the best model to use in clinical practice Moreover, individually, these models present some weaknesses, such as the inability to deal with missing information. This work addresses these problems, proposing a Bayesian classifier strategy enabling the simultaneous use of several models (models' fusion). Thus, a higher number of risk factors can be used in the common model, while it can deal with missing information. The validation of the strategy is carried out through the combination of three current risk score models (GRACE, TIMI, PURSUIT). Results were obtained based on a dataset that comprises 460 consecutive patients admitted to the Cardiology Department of Santa Cruz Hospital, Lisbon, from 1999 to 2001. A comparison with the voting scheme, which considers exclusively the outputs of models to combine (models output combination) is also carried out. The proposed Bayesian approach had very satisfactory results, confirming the potential of its application to the clinical practice.
authors.affiliation: Instituto Politécnico de Coimbra, Departamento de Engenharia Informática e de Sistemas, Rua Pedro Nunes, 3030-199 Coimbra. sparedes@isec.pt
authors.forename: S
authors.initials: S
authors.lastname: Paredes
authors.forename: T
authors.initials: T
authors.lastname: Rocha
authors.forename: P
authors.initials: P
authors.lastname: de Carvalho
authors.forename: J
authors.initials: J
authors.lastname: Henriques
authors.forename: D
authors.initials: D
authors.lastname: Rasteiro
authors.forename: J
authors.initials: J
authors.lastname: Morals
authors.forename: J
authors.initials: J
authors.lastname: Ferreira
authors.forename: M
authors.initials: M
authors.lastname: Mendes
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000175:diagnosis / Q000401:mortality*; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011174:Portugal / Q000453:epidemiology; D011379:Prognosis; D016016:Proportional Hazards Models; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D016019:Survival Analysis; D015996:Survival Rate