DocumentCode
2031421
Title
Toward an optimal use of artificial intelligence techniques within a clinical decision support system
Author
Aljaaf, Ahmed J. ; Al-Jumeily, Dhiya ; Hussain, Abir J. ; Fergus, Paul ; Al-Jumaily, Mohammed ; Abdel-Aziz, Khaled
Author_Institution
Appl. Comput. Res. Group, Liverpool John Moores Univ., Liverpool, UK
fYear
2015
fDate
28-30 July 2015
Firstpage
548
Lastpage
554
Abstract
Intelligent clinical decision support systems have been increasingly used in health care organisations. These systems are intended to help physicians in their diagnosis procedures; making decisions more accurate and effective, minimising medical errors, improving patient safety and reducing costs. However, the effectiveness and accuracy of these systems largely depend on the underlying AI technique that has been used, where same clinical-related problem can be solved using more than one AI technique which may provide different outcomes. Consequently, it is crucial to figure out the ideal utilisation of AI techniques in the clinical decision support systems. Our research study reviews various researches which utilised Artificial Intelligence techniques in clinical decision support systems with the aim of identifying basic criterion for adequate use of intelligent techniques within such systems. This paper presents a yes/no inquiry approach based on observations of previous research studies. The objective of this inquiry is to facilitate the selection of the most beneficial and effective AI technique that can be applied in the medical decision support system to provide the best outcomes.
Keywords
artificial intelligence; decision support systems; medical information systems; patient care; AI technique; artificial intelligence techniques; clinical-related problem; cost reduction; health care organisations; intelligent clinical decision support systems; medical decision support system; medical errors; patient safety; yes-no inquiry approach; Accuracy; Decision support systems; Diseases; Knowledge based systems; Medical diagnostic imaging; artificial intelligence; clinical decision support; medical errors;
fLanguage
English
Publisher
ieee
Conference_Titel
Science and Information Conference (SAI), 2015
Conference_Location
London
Type
conf
DOI
10.1109/SAI.2015.7237196
Filename
7237196
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