Heart Failure Decision Support System Using Semantic Web Approach

Heart failure is a health problem that continues to grow in the world with the number of heart failure patients more than 20 million people. The mortality rate caused by heart failure, especially in Indonesia is quite high due to indifference to symptoms of heart failure. An expert system is needed that is used to predict heart failure and provide a decision support for doctors to take action on patients with heart failure. This paper is a systematic literature review that provides insights related to the semantic method used to heart failure decision support. The methodology used in this study includes (1) defining the research questions; (2) defining the literature search strategy; (3) defining the study selection criteria; (4) study quality assessment; and (5) data extraction and synthesis. Based on the results of a systematic literature review, several semantic methods such as Ontology, SWRL, and Bayesian networks are used in making a support system for heart failure. There are some features that are used in predicting heart failure such as patient information, symptoms, blood test, ECG, etc.