6533b82dfe1ef96bd12912a7

RESEARCH PRODUCT

Expert system for predicting unstable angina based on Bayesian networks

Emilio Soria-olivasAntonio J. SerranoJuan SanchisMarcelino Martínez-soberSilvia VenturaClara BonanadJoan Vila-francés

subject

education.field_of_studyUnstable anginaComputer sciencebusiness.industryPopulationGeneral EngineeringBayesian networkcomputer.software_genremedicine.diseaseClinical decision support systemExpert systemComputer Science ApplicationsArtificial IntelligencemedicineWeb applicationData miningeducationbusinesscomputer

description

The use of computer-based clinical decision support (CDS) tools is growing significantly in recent years. These tools help reduce waiting lists, minimise patient risks and, at the same time, optimise the cost health resources. In this paper, we present a CDS application that predicts the probability of having unstable angina based on clinical data. Due to the characteristics of the variables (mostly binary) a Bayesian network model was chosen to support the system. Bayesian-network model was constructed using a population of 1164 patients, and subsequently was validated with a population of 103 patients. The validation results, with a negative predictive value (NPV) of 91%, demonstrate its applicability to help clinicians. The final model was implemented as a web application that is currently been validated by clinician specialists.

yearjournalcountryeditionlanguage
2013-09-01Expert Systems with Applications
https://doi.org/10.1016/j.eswa.2013.03.029