Clinical Decision Support System Based on KNN/Ontology Extraction Method

Abstract

The complexity of the knowledge structure in the clinical cases, involving a wide range of attributes, results in making its case similarity calculation more complex. The existing medical ontologies, due to different expressions of the same concepts in computer information retrieval, causes difficulties in terms of sharing useful information in different database systems. This paper constructs a new decision support system based on KNN/ontology method was proposed. The detail of the methods and processes of common clinical case knowledge acquisition in combination with the method of obtaining structured information has been presented. The clinical case data similarity calculation method based on various types such as symptom information, medical history information, complications, surgical information, diagnostic results and other information, for record of a clinical diagnosis and treatment process. The validity of the similarity calculation method and the weight calculation method is verified by the clinical case data. The proposed methods can be effective for improving the quality and level of clinical services for medical service organizations.