MINING OF HEALTH INFORMATION FROM ONTOLOGIES

Maja Hadzic, Fedja Hadzic, Tharam Dillon

Abstract

Data mining techniques can be used to efficiently analyze semi-structured data. Semi-structured data are predominantly used within the health domain as they enable meaningful representations of the health information. Tree mining algorithms can efficiently extract frequent substructures from semi-structured knowledge representations. In this paper, we demonstrate application of the tree mining algorithms on the health information. We illustrate this on an example of Human Disease Ontology (HDO) which represents information about diseases in 4 ‘dimensions’: (1) disease types, (2) phenotype (observable characteristics of an organism) or symptoms (3) causes related to the disease, namely genetic causes, environmental causes or micro-organisms, and (4) treatments available for the disease. The extracted data patterns can provide useful information to help in disease prevention, and assist in delivery of effective and efficient health services.

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Paper Citation


in Harvard Style

Hadzic M., Hadzic F. and Dillon T. (2008). MINING OF HEALTH INFORMATION FROM ONTOLOGIES . In Proceedings of the First International Conference on Health Informatics - Volume 2: HEALTHINF, (BIOSTEC 2008) ISBN 978-989-8111-16-6, pages 155-160. DOI: 10.5220/0001040801550160


in Bibtex Style

@conference{healthinf08,
author={Maja Hadzic and Fedja Hadzic and Tharam Dillon},
title={MINING OF HEALTH INFORMATION FROM ONTOLOGIES},
booktitle={Proceedings of the First International Conference on Health Informatics - Volume 2: HEALTHINF, (BIOSTEC 2008)},
year={2008},
pages={155-160},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001040801550160},
isbn={978-989-8111-16-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Health Informatics - Volume 2: HEALTHINF, (BIOSTEC 2008)
TI - MINING OF HEALTH INFORMATION FROM ONTOLOGIES
SN - 978-989-8111-16-6
AU - Hadzic M.
AU - Hadzic F.
AU - Dillon T.
PY - 2008
SP - 155
EP - 160
DO - 10.5220/0001040801550160