Ontology-driven adaptive medical information collection system

Matt Mouley Bouamrane; Alan Rector; Martin Hurrell

Ontology-driven adaptive medical information collection system

Matt Mouley Bouamrane, Alan Rector, Martin Hurrell

Research output: Chapter in Book/Conference proceeding › Conference contribution

Abstract

Computer-based surveys and questionnaires have become ubiquitous. Yet in many cases, Information Collection Systems (ICS) offer limited support in terms of tailoring structure and content of surveys in response to user interaction. Previous techniques for content adaptation such as conditional branching do not scale well and are also hard to maintain as structural dependencies in a survey often need to be hard-coded in the system. We here propose a generic model for context-sensitive self adaptation of ICS, based on a questionnaire ontology. We illustrate the model with a description of our own medical ICS implementation and discuss the potential benefits of such system, especially in the context of tailored healthcare. © 2008 Springer-Verlag Berlin Heidelberg.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\|Lect. Notes Comput. Sci.
Publisher	Springer Nature
Pages	574-584
Number of pages	10
Volume	4994
ISBN (Print)	3540681221, 9783540681229
Publication status	Published - 2008
Event	17th International Symposium on Methodologies for Intelligent Systems, ISMIS 2008 - Toronto Duration: 1 Jul 2008 → …

Conference

Conference	17th International Symposium on Methodologies for Intelligent Systems, ISMIS 2008
City	Toronto
Period	1/07/08 → …

Keywords

Computer Science, Artificial Intelligence

Cite this

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title = "Ontology-driven adaptive medical information collection system",

abstract = "Computer-based surveys and questionnaires have become ubiquitous. Yet in many cases, Information Collection Systems (ICS) offer limited support in terms of tailoring structure and content of surveys in response to user interaction. Previous techniques for content adaptation such as conditional branching do not scale well and are also hard to maintain as structural dependencies in a survey often need to be hard-coded in the system. We here propose a generic model for context-sensitive self adaptation of ICS, based on a questionnaire ontology. We illustrate the model with a description of our own medical ICS implementation and discuss the potential benefits of such system, especially in the context of tailored healthcare. {\textcopyright} 2008 Springer-Verlag Berlin Heidelberg.",

keywords = "Computer Science, Artificial Intelligence",

author = "Bouamrane, \{Matt Mouley\} and Alan Rector and Martin Hurrell",

note = "Natl, Sci Bouamrane, Matt-Mouley Rector, Alan Hurrell, Martin 11 BERLIN BHS99; 17th International Symposium on Methodologies for Intelligent Systems, ISMIS 2008 ; Conference date: 01-07-2008",

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language = "English",

isbn = "3540681221",

volume = "4994",

pages = "574--584",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.",

publisher = "Springer Nature",

address = "United States",

}

Bouamrane, MM, Rector, A & Hurrell, M 2008, Ontology-driven adaptive medical information collection system. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. vol. 4994, Springer Nature, pp. 574-584, 17th International Symposium on Methodologies for Intelligent Systems, ISMIS 2008, Toronto, 1/07/08.

Ontology-driven adaptive medical information collection system. / Bouamrane, Matt Mouley; Rector, Alan; Hurrell, Martin.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 4994 Springer Nature, 2008. p. 574-584.

Research output: Chapter in Book/Conference proceeding › Conference contribution

TY - GEN

T1 - Ontology-driven adaptive medical information collection system

AU - Bouamrane, Matt Mouley

AU - Rector, Alan

AU - Hurrell, Martin

N1 - Natl, Sci Bouamrane, Matt-Mouley Rector, Alan Hurrell, Martin 11 BERLIN BHS99

PY - 2008

Y1 - 2008

N2 - Computer-based surveys and questionnaires have become ubiquitous. Yet in many cases, Information Collection Systems (ICS) offer limited support in terms of tailoring structure and content of surveys in response to user interaction. Previous techniques for content adaptation such as conditional branching do not scale well and are also hard to maintain as structural dependencies in a survey often need to be hard-coded in the system. We here propose a generic model for context-sensitive self adaptation of ICS, based on a questionnaire ontology. We illustrate the model with a description of our own medical ICS implementation and discuss the potential benefits of such system, especially in the context of tailored healthcare. © 2008 Springer-Verlag Berlin Heidelberg.

AB - Computer-based surveys and questionnaires have become ubiquitous. Yet in many cases, Information Collection Systems (ICS) offer limited support in terms of tailoring structure and content of surveys in response to user interaction. Previous techniques for content adaptation such as conditional branching do not scale well and are also hard to maintain as structural dependencies in a survey often need to be hard-coded in the system. We here propose a generic model for context-sensitive self adaptation of ICS, based on a questionnaire ontology. We illustrate the model with a description of our own medical ICS implementation and discuss the potential benefits of such system, especially in the context of tailored healthcare. © 2008 Springer-Verlag Berlin Heidelberg.

KW - Computer Science, Artificial Intelligence

UR - https://www.scopus.com/pages/publications/44649195655

M3 - Conference contribution

SN - 3540681221

SN - 9783540681229

VL - 4994

SP - 574

EP - 584

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.

PB - Springer Nature

T2 - 17th International Symposium on Methodologies for Intelligent Systems, ISMIS 2008

Y2 - 1 July 2008

ER -

Ontology-driven adaptive medical information collection system

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