Title :
Designing knowledge representation framework for ICD-10
Author :
Kharadkar, Ronak ; Justus, S.
Author_Institution :
Sch. of Comput. Sci. & Eng., VIT Univ., Chennai, India
Abstract :
Knowledge Representation (KR) is the field related Artificial Intelligence which basically deals with the usage of formal symbols which are used to represent a collection of proposition believed by putative agents. In KR we deal with two types of representations Symbol and Concept level representations. ICD-10 is the 10th revision of the International Statistical Classification of Diseases and Health related problems. Its primary job is to code for diseases, symptoms, complaints and external causes of injury. It uses a 7-bit code to represent all diseases. The main focus of our research work is that we are going to represent the 7 bit code into a logical unit and logical entailments to form conceptual relations among them.
Keywords :
diseases; knowledge representation languages; medical information systems; ICD-10; International Statistical Classification of Diseases and Health; KR; OWL; artificial intelligence; complaint code; concept level representation; conceptual relations; diseases code; external injury cause code; formal symbols; knowledge representation framework design; logical entailments; logical unit; proposition collection representation; putative agents; symbol representation; symptom code; Diseases; Knowledge based systems; Knowledge management; Market research; OWL; Ontologies; CG; DL; ICD-10; Knowledgebase; OWL;
Conference_Titel :
Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8432-9
DOI :
10.1109/ABLAZE.2015.7154927