Designing Ontology-Based Knowledge Integration for Preprocessing of Medical Data in Enhancing a Machine Learning System for Coding Assignment of a Multi-Label Medical Text
This paper discusses the designing of knowledge
integration of clinical information extracted from distributed medical
ontologies in order to ameliorate a machine learning-based multilabel
coding assignment system. The proposed approach is
implemented using a decision tree technique of the machine learning
on the university hospital data for patients with Coronary Heart
Disease (CHD). The preliminary results obtained show a satisfactory
finding that the use of medical ontologies improves the overall
 Sebastiani, F. (2002). Machine learning in automated text categorization.
ACM Comput. Surv., 34(1), 1-47.
 Nelson, S.J., et al. (2001). Relationships in medical subject headings. In
C.A. Bean & R. Green (Eds.), Relationship in the Organization of
Knowledge. New York: Kluwer Academic Publishers, (pp. 171-184).
 Gruber, T. (1995). Toward Principles for the Design of Ontologies used
for Knowledge Sharing. International Journal of Human-Computer
Studies, 43, 907-928.
 WHO. World Health Organization. www.who.int, www.who.int/
 Martin-Valdivia, M.T. (2009) Expanding terms with medical ontologies
to improve a multi-label text categorization system. In P.Violaine and R.
Mathieu (Eds.), Information Rerieval in Biomedicine: Natural Language
Processing for Knowledge Integration, (pp 38-57).
 Bhogal, J., et al. (2007) A review of ontology based query expansion.
Information Processing & Management, 43(4), July 2007, 866-886.
 Waraporn, P. (2008). Proposed framework for interpreting medical
diagnosis records using adopted WordNet/Medical WordNet.
Proceedings of Technology and Innovation for Sustainable Development
Conference (TISD2008), 05_004_2008I, 433-436.
 Waraporn, P. (2008). Distributed Ontological Engineering and Integrated
Development of Medical Diagnosis Coding Ontology for State Hospitals
in Thailand, Proceedings of National Conference on Computer and
Information Technology (NCIT 2008).