Title :
An Ontology model-based ECG diagnostic solution
Author_Institution :
Doctoral Sch. of Appl. Inf., Obuda Univ., Budapest, Hungary
Abstract :
In this paper the authors present an ECG diagnostic method based on an Ontology model. The modeled knowledge base is backed by the Minnesota Code which is a rule-based system for the evaluation of reference ECG signals. The paper presents a possible method to improve the crisp value based rule hierarchy system of the Minnesota Code by abstracting the strict value parts of the diagnostic system and provide support for partial diagnostic results. The presented approach preserves the original key concepts of the diagnostic logic and provides an improved structure for information gathering and handling real-world problems while using ontology reasoning to provide diagnostic results.
Keywords :
electrocardiography; inference mechanisms; knowledge based systems; medical signal processing; ontologies (artificial intelligence); patient diagnosis; ECG signal; Minnesota code; diagnostic logic; diagnostic system; information gathering; knowledge base model; ontology model-based ECG diagnostic solution; ontology reasoning; rule hierarchy system; rule-based system;
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2012 IEEE 13th International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4673-5205-5
Electronic_ISBN :
978-1-4673-5210-9
DOI :
10.1109/CINTI.2012.6496758