Bringing Bayesian networks to bedside: a web-based framework

Raphael Oliveira1, Joana Ferreira1, Diogo Libânio1, Claudia Camila Dias1, Pedro Pereira Rodrigues1

1CINTESIS – Center for Health Technology and Services Research, Faculty of Medicine of the University of Porto Porto, Portugal

The use of statistical methods and quantitative analysis in the clinical decision-making process, is one of the ways of using the latest scientific evidence. Despite its advantages, the availability of inference software in clinical settings is still limited. Typically, in prognostic or diagnostic models, support systems are based in logistic or linear regression. These techniques have the advantage of being easily interpretable from the clinical point of view, having nonetheless a poor graphical representation. However, the nature of biomedical data requires the application of techniques that go beyond traditional biostatistics, such as Bayesian networks. Bayesian approaches have an extreme importance in clinical problems, since they provide both qualitative and quantitative perspectives. They consider prior knowledge, making data analysis an update processing of prior knowledge with observed evidence. To potentiate the use of the statistical methods within the daily practice, we created simple web forms. These web forms do not require complex interactions, receiving clinical inputs and transmitting them to a Bayesian network inference engine. The information is processed by the engine and the output data is sent to the end-user through the same web form. This approach makes the derived models usable at bedside by both the clinicians and the patients themselves.

keywords: web-based forms; Bayesian models; clinical use

Poster: Bringing Bayesian networks to bedside: a web-based framework