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Similarity of Medical Cases in Health Care Using Cosine Similarity and Ontology

Fulltext:


Authors:

Shahina Begum, Mobyen Uddin Ahmed, Peter Funk, Ning Xiong, Bo von Schéele

Research group:

Artificial Intelligence and Intelligent Systems

Publication Type:

Conference/Workshop Paper

Venue:

5th Workshop on CBR in the Health Sciences, ICCBR-07

Publisher:

Springer LNCS

Abstract

The increasing use of digital patient records in hospital saves both time and reduces risks wrong treatments caused by lack of information. Digital patient records also enable efficient spread and transfer of experience gained from diagnosis and treatment of individual patient. This is today mostly manual (speaking with col-leagues) and rarely aided by computerized system. Most of the content in patient re-cords is semi-structured textual information. In this paper we propose a hybrid tex-tual case-based reasoning system promoting experience reuse based on structured or unstructured patient records, case-based reasoning and similarity measurement based on cosine similarity metric improved by a domain specific ontology and the nearest neighbor method. Not only new cases are learned, hospital staff can also add comments to existing cases and the approach enables prototypical cases.

Bibtex

@inproceedings{Begum964,
author = {Shahina Begum and Mobyen Uddin Ahmed and Peter Funk and Ning Xiong and Bo von Sch{\'e}ele},
title = {Similarity of Medical Cases in Health Care Using Cosine Similarity and Ontology},
editor = {David C. Wilson and Deepak Khemani},
pages = {263--272},
month = {August},
year = {2007},
booktitle = {5th Workshop on CBR in the Health Sciences, ICCBR-07},
publisher = {Springer LNCS},
url = {http://www.es.mdu.se/publications/964-}
}