An Ontology-based Bayesian Network Approach for Representing Uncertainty in Clinical Practice Guidelines

3rd ISWC Workshop on Uncertainty Reasoning for the Semantic Web

Hai-tao Zheng ; Bo-Yeong Kang ; Hong-Gee Kim

Others  :  http://CEUR-WS.org/Vol-327/paper8.pdf
PID  :  22311

来源: CEUR

【 摘 要 】

Clinical Practice Guidelines (CPGs) play an important rolein improving the quality of care and patient outcomes. Although sev- eral machine-readable representations of practice guidelines implemented with semantic web technologies have been presented, there is no imple- mentation to represent uncertainty with respect to activity graphs in clinical practice guidelines. In this paper, we are exploring a Bayesian Network(BN) approach for representing the uncertainty in CPGs based on ontologies. Based on the representation of uncertainty in CPGs, when an activity occurs, we can evaluate its e®ect on the whole clinical pro- cess, which, in turn, can help doctors judge the risk of uncertainty for other activities, and make a decision. A variable elimination algorithm is applied to implement the BN inference and a validation of an aspirin