A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom
Clinical decision support system (CDSS) is promising in assisting physicians for improving decision making process and facilitates healthcare services. In medicine, causality has become the main concern throughout healthcare and decision-making. Causality is necessary for understanding all structure...
Saved in:
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Teknologi MARA, Perlis
2019
|
Subjects: | |
Online Access: | http://ir.uitm.edu.my/id/eprint/41829/1/41829.pdf http://ir.uitm.edu.my/id/eprint/41829/ https://jurnalintelek.uitm.edu.my/index.php/main |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uitm.ir.41829 |
---|---|
record_format |
eprints |
spelling |
my.uitm.ir.418292021-02-26T01:37:43Z http://ir.uitm.edu.my/id/eprint/41829/ A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom Rahim, Nur Raidah Nordin, Sharifalillah Mohd Dom, Rosma Expert systems (Computer science). Fuzzy expert systems Computer applications to medicine. Medical informatics Clinical decision support system (CDSS) is promising in assisting physicians for improving decision making process and facilitates healthcare services. In medicine, causality has become the main concern throughout healthcare and decision-making. Causality is necessary for understanding all structures of scientific reasoning and for providing a coherent and sufficient explanation for any event. However, there are lack of existing CDSS that provide causal reasoning for the presented outcomes or decisions. These are necessary for showing reliability of the outcomes, and helping the physicians in making proper decisions. In this study, an ontology-based CDSS model is developed based on several key concepts and features of causality and graphical modeling techniques. For the evaluation process, the Pellet reasoner is used to evaluate the consistency of the developed ontology model. In addition, an evaluation tool known as Ontology Pitfall Scanner is used for validating the ontology model through pitfalls detection. The developed ontology-based CDSS model has potentials to be applied in clinical practice and helping the physicians in decision-making process. Universiti Teknologi MARA, Perlis 2019-12 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/41829/1/41829.pdf Rahim, Nur Raidah and Nordin, Sharifalillah and Mohd Dom, Rosma (2019) A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom. Jurnal Intelek, 14 (2). pp. 187-197. ISSN 2231-7716 https://jurnalintelek.uitm.edu.my/index.php/main |
institution |
Universiti Teknologi Mara |
building |
Tun Abdul Razak Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Mara |
content_source |
UiTM Institutional Repository |
url_provider |
http://ir.uitm.edu.my/ |
language |
English |
topic |
Expert systems (Computer science). Fuzzy expert systems Computer applications to medicine. Medical informatics |
spellingShingle |
Expert systems (Computer science). Fuzzy expert systems Computer applications to medicine. Medical informatics Rahim, Nur Raidah Nordin, Sharifalillah Mohd Dom, Rosma A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom |
description |
Clinical decision support system (CDSS) is promising in assisting physicians for improving decision making process and facilitates healthcare services. In medicine, causality has become the main concern throughout healthcare and decision-making. Causality is necessary for understanding all structures of scientific reasoning and for providing a coherent and sufficient explanation for any event. However, there are lack of existing CDSS that provide causal reasoning for the presented outcomes or decisions. These are necessary for showing reliability of the outcomes, and helping the physicians in making proper decisions. In this study, an ontology-based CDSS model is developed based on several key concepts and features of causality and graphical modeling techniques. For the evaluation process, the Pellet reasoner is used to evaluate the consistency of the developed ontology model. In addition, an evaluation tool known as Ontology Pitfall Scanner is used for validating the ontology model through pitfalls detection. The developed ontology-based CDSS model has potentials to be applied in clinical practice and helping the physicians in decision-making process. |
format |
Article |
author |
Rahim, Nur Raidah Nordin, Sharifalillah Mohd Dom, Rosma |
author_facet |
Rahim, Nur Raidah Nordin, Sharifalillah Mohd Dom, Rosma |
author_sort |
Rahim, Nur Raidah |
title |
A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom |
title_short |
A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom |
title_full |
A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom |
title_fullStr |
A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom |
title_full_unstemmed |
A clinical decision support system based on ontology and causal reasoning models / Nur Raidah Rahim, Sharifalillah Nordin and Rosma Mohd Dom |
title_sort |
clinical decision support system based on ontology and causal reasoning models / nur raidah rahim, sharifalillah nordin and rosma mohd dom |
publisher |
Universiti Teknologi MARA, Perlis |
publishDate |
2019 |
url |
http://ir.uitm.edu.my/id/eprint/41829/1/41829.pdf http://ir.uitm.edu.my/id/eprint/41829/ https://jurnalintelek.uitm.edu.my/index.php/main |
_version_ |
1692994644108902400 |
score |
13.214269 |