Back to Search Start Over

Semantic-Rich Recommendation System for Medical Emergency Response System

Authors :
Karthika, R.
Deborah, L.
Zheng, Wenying
Alqahtani, Fayez
Tolba, Amr
Krishnan, B.
Bansal, Ritika
Source :
International Journal on Semantic Web and Information Systems; December 2023, Vol. 20 Issue: 1 p1-18, 18p
Publication Year :
2023

Abstract

The emergency response process consists of methodical and coordinated series of actions and protocols executed by individuals and organizations to proficiently address crises. When planning for medical emergencies, it is vital to work with responsive medical organizations to ensure good communication and coordination. Unlike e-government processes, emergency response processes are focused on knowledge and may frequently change as the emergency situation develops. It is important to change the emergency response plan for dynamic situations and the proposed method helps to create a flexible plan for emergency responses. The proposed approach uses a system for organizing knowledge to figure out the needs and the resources essential for an emergency. It helps to identify the organizations to be involved based on their rules for mutual aid and jurisdiction. Experimental analysis shows that the proposed method outperforms Smart-c and DCERP in suggesting a greater number of hospitals during medical emergency and achieves 0.8, 0.9 and 0.9 precision, recall, and f-measure approximately.

Details

Language :
English
ISSN :
15526283 and 15526291
Volume :
20
Issue :
1
Database :
Supplemental Index
Journal :
International Journal on Semantic Web and Information Systems
Publication Type :
Periodical
Accession number :
ejs65911537
Full Text :
https://doi.org/10.4018/IJSWIS.341231