Ontology-supported processing of clinical text using medical knowledge integration for multi-label classification of diagnosis coding

Abstract--This paper discusses the knowledge integration of clinical information extracted from distributed medical ontology in order to ameliorate a machine learning-based multi-label coding assignment system. The proposed approach is implemented using a decision tree based cascade hierarchical technique on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding. An ontology is a specification of a conceptualization that defines and/or specifies the concepts, relationships, and other distinctions that are relevant for modeling a domain. Such specification takes the form of the definitions of representational vocabulary (classes, relations, and so on), which provide meanings to the vocabulary and formal constraints on its coherent use [3].