Advanced search ?

Object

Download

Title: An Ontological Framework for Representing Clinical Knowledge in Decision Support Systems, Journal of Telecommunications and Information Technology, 2014, nr 1

Creator:

Iannaccone, Marco ; Esposito, Massimo

Date:

2014, nr 1

Resource Type:

artykuł

Description:

In the last decades, clinical evidence and expert consensus have been encoded into advanced Decision Support Systems (DSSs) in order to promote a better integration into the clinical workflow and facilitate the automatic provision of patient specific advice at the time and place where decisions are made. However, clinical knowledge, typically expressed as unstructured and free text guidelines, requires to be encoded into a computer interpretable form suitable for being interpreted and processed by DSSs. For this reason, this paper proposes an ontological framework, which enables the encoding of clinical guidelines from text to a formal representation, in order to allow querying, advanced reasoning and management in a well defined and rigorous way. In particular, it jointly manages declarative and procedural aspects of a standards based verifiable guideline model, named GLM-CDS (GuideLine Model for Clinical Decision Support), and expresses reasoning tasks that exploit such a represented knowledge in order to formalize integrity constraints, business rules and complex inference rules.

Publisher:

Instytut Łączności - Państwowy Instytut Badawczy, Warszawa

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:1662

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

Decision Support Systems Unstructured Data Rules Clinical Practice Guidelines Ontology

Object collections:

Last modified:

Jul 24, 2014

In our library since:

Jul 24, 2014

Number of object content hits:

74

All available object's versions:

https://bc.itl.waw.pl/publication/1937

Show description in RDF format:

RDF

Show description in OAI-PMH format:

OAI-PMH

Edition name Date
Iannaccone, Marco; Esposito, Massimo, An Ontological Framework for Representing Clinical Knowledge in Decision Support Systems, Journal of Telecommunications and Information Technology, 2014, nr 1 Jul 24, 2014

Objects Similar
Data mining and complex telecommunications problems modeling, Journal of Telecommunications and Information Technology, 2003, nr 3

Granat, Janusz

2003, nr 3
artykuł
Improving interpretability: combined use of LVQ and ARTMAP in decision support, Journal of Telecommunications and Information Technology, 2005,nr 4

Raffone, Antonino Giorgi, Andrea Kwok, Hoi Fei

2005, nr 4
artykuł
Heuristic Analysisof Transport System Efficiency Basedon Movement of Mobile Network Users, Journal of Telecommunications and Information Technology, 2009, nr 3

Sabak, Grzegorz

2009, nr 3
artykuł
Intelligent decision system based on the evidential reasoning approach and its applications, Journal of Telecommunications and Information Technology, 2005, nr 3

Yang, Jian-Bo Xu, Dong-Ling

2005, nr 3
artykuł
Rough set theory and its applications, Journal of Telecommunications and Information Technology, 2002, nr 3

Pawlak, Zdzisław

2002, nr 3
artykuł
Assessing Coastal Sustainability: A Bayesian Approach for Modeling and Estimating a Global Index for Measuring Risk, Journal of Telecommunications and Information Technology, 2013, nr 4

Gaglio, Salvatore Vitabile, Salvatore Pernice, Giuseppe Farruggia, Alfonso

2013, nr 4
artykuł
Reference distribution based decision support platform, Journal of Telekommunications and Information Technology, 2008, nr 3

Ogryczak, Włodzimierz Bareja, Krzysztof

2008, nr 3
artykuł
Structural representations of unstructured knowledge, Journal of Telecommunications and Information Technology, 2005, nr 3

Traczyk, Wiesław

2005, nr 3
artykuł
More
×

Citation

Citation style:

Contact details

Address

Instytut Łączności – Państwowy Instytut Badawczy ul. Szachowa 1 04-894 Warszawa

Phone

(+48) 5128 696

E-Mail

biblioteka@il-pib.pl

Visit us!

This page uses 'cookies'. More information