Cardiovascular Event Risk Assessment – Fusion of Individual Risk Assessment Tools Applied to the Portuguese Population



Cardiovascular disease (CVD) is the world’s largest killer, responsible for 17.1 million deaths per year. Thus, the improvement of the prognosis of this disease is an important factor to defeat the current statistics. Although there are several risk tools available to assess the risk of occurrence of a cardiovascular event within a given period of time, these tools present some major drawbacks. In particular, each individual tool considers a reduced number of risk factors, does not permit to incorporate additional clinical knowledge and presents difficulties in coping with missing risk factors.
In order to overcome the identified weaknesses, a flexible framework is proposed here, based on the fusion of a set of distinct risk assessment tools. The methodology is based on two main hypotheses: i) it is possible to derive a common representation for the individual risk assessment tools, ii) it is possible to combine (fusion) the obtained individual models, in order to achieve the referred goals. Additionally, through the implementation of optimization techniques, an increasing in the global risk prediction performance is also investigated.
The validation of the strategy is carried out through the combination of three current risk assessment tools (GRACE, TIMI, PURSUIT) developed to predict the risk of an event in coronary artery disease (CAD) patients. The combination of these tools is validated with two real patients testing datasets: i) Santa Cruz Hospital, Lisbon/Portugal, N=460 ACS-NSTEMI patients; ii) Santo André Hospital, Leiria/Portugal, N=99 ACS-NSTEMI patients.
Considering the obtained results with the available datasets it is possible to state that the initial goals of this work were achieved. This evidence makes this work a valid contribution for the improvement of the risk assessment applied to cardiovascular diseases.


Cardiovascular risk assessment, Bayesian classifiers, Models' fusion


Cardiovascular risk assessment

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15th International Conference on Information Fusion, 2012, July 2012

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