Acute asthma severity identification of expert system flow in emergency department
Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based rea...
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creator | Sharif, Nurul Atikah Mohd Ahmad, Norazura Ahmad, Nazihah Desa, Wan Laailatul Hanim Mat |
description | Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic. |
doi_str_mv | 10.1063/1.5012215 |
format | Conference Proceeding |
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subjects | Asthma Decision making Documentation Embedded systems Emergency management Emergency medical services Emergency services Expert systems Fuzzy logic Support systems |
title | Acute asthma severity identification of expert system flow in emergency department |
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