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

Fariba Shadabi; Dharmendra Sharma

doi:10.1109/ICFCC.2009.140

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

Fariba Shadabi
, Dharmendra Sharma

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

5 Citations (Scopus)

66 Downloads (Pure)

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 language	English
Title of host publication	Proceedings: 2009 International Conference on Future Computer and Communication, ICFCC 2009
Place of Publication	Danvers, USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	540-542
Number of pages	3
ISBN (Print)	9780769535913
DOIs	https://doi.org/10.1109/ICFCC.2009.140
Publication status	Published - 2009
Event	2009 International Conference on Future Computer and Communication, ICFCC 2009 - Kuala Lumpar, Malaysia Duration: 3 Apr 2009 → 5 Apr 2009

Conference

Conference	2009 International Conference on Future Computer and Communication, ICFCC 2009
Country/Territory	Malaysia
City	Kuala Lumpar
Period	3/04/09 → 5/04/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.1109/ICFCC.2009.140

Conference ProceedingFinal published version, 190 KB

Cite this

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title = "Using knowledge and rule induction methods for enhancing clinical diagnosis: Success stories",

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.",

author = "Fariba Shadabi and Dharmendra Sharma",

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language = "English",

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pages = "540--542",

booktitle = "Proceedings: 2009 International Conference on Future Computer and Communication, ICFCC 2009",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2009 International Conference on Future Computer and Communication, ICFCC 2009 ; Conference date: 03-04-2009 Through 05-04-2009",

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Shadabi, F & Sharma, D 2009, Using knowledge and rule induction methods for enhancing clinical diagnosis: Success stories. in Proceedings: 2009 International Conference on Future Computer and Communication, ICFCC 2009. IEEE, Institute of Electrical and Electronics Engineers, Danvers, USA, pp. 540-542, 2009 International Conference on Future Computer and Communication, ICFCC 2009, Kuala Lumpar, Malaysia, 3/04/09. https://doi.org/10.1109/ICFCC.2009.140

Using knowledge and rule induction methods for enhancing clinical diagnosis: Success stories. / Shadabi, Fariba; Sharma, Dharmendra.
Proceedings: 2009 International Conference on Future Computer and Communication, ICFCC 2009. Danvers, USA: IEEE, Institute of Electrical and Electronics Engineers, 2009. p. 540-542.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

TY - GEN

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AU - Shadabi, Fariba

AU - Sharma, Dharmendra

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

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U2 - 10.1109/ICFCC.2009.140

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M3 - Conference contribution

AN - SCOPUS:70449385021

SN - 9780769535913

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EP - 542

BT - Proceedings: 2009 International Conference on Future Computer and Communication, ICFCC 2009

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Danvers, USA

Y2 - 3 April 2009 through 5 April 2009

ER -

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

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