Using knowledge and rule induction methods for enhancing clinical diagnosis: Success stories

Fariba Shadabi, Dharmendra Sharma

Research output: A Conference proceeding or a Chapter in BookConference contribution

4 Citations (Scopus)

Abstract

The economic and social benefits of accurately predicting medical outcomes are very high. As a result, the problem of improving predictive models has attracted many researchers. Over the past few years there has been great interest in the use of advance knowledge discover techniques to mimic human functions. Research shows that such techniques can be applied in healthcare environments where an automated process must improve its performance based on previous data, adapt to changes and deal with uncertain and incomplete medical knowledge. The underlying purpose of this paper is to illustrate the utility of combining multi agent approach and hybrid machine learning and data mining techniques for producing predictive classifiers in clinical settings, through a few real world success stories.

Original languageEnglish
Title of host publicationProceedings: 2009 International Conference on Future Computer and Communication, ICFCC 2009
Place of PublicationDanvers, USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages540-542
Number of pages3
ISBN (Print)9780769535913
DOIs
Publication statusPublished - 2009
Event2009 International Conference on Future Computer and Communication, ICFCC 2009 - Kuala Lumpar, Malaysia
Duration: 3 Apr 20095 Apr 2009

Conference

Conference2009 International Conference on Future Computer and Communication, ICFCC 2009
CountryMalaysia
CityKuala Lumpar
Period3/04/095/04/09

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