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Missing information prediction in ripple down rule based clinical decision support system
conference contribution
posted on 2023-05-23, 14:32 authored by Hussain, M, Hassan, AU, Sadiq, M, Byeong KangByeong Kang, Lee, SClinical Decision Support System (CDSS) plays an indispensable role in decision making and solving complex problems in the medical domain. However, CDSS expects complete information to deliver an appropriate recommendation. In real scenarios, the user may not be able to provide complete information while interacting with CDSS. Therefore, the CDSS may fail to deliver accurate recommendations. The system needs to predict and complete missing information for generating appropriate recommendations. In this research, we extended Ripple Down Rules (RDR) methodology that identifies the missing information in terms of key facts by analyzing similar previous patient cases. Based on identified similar cases, the system requests the user about the existence of missing facts. According to the user’s response, the system resumes current case and infers the most appropriate recommendation. Alternatively, the system generates an initial recommendation based on provided partial information.
History
Publication title
Smart Homes and Health Telematics: Designing a Better Future: Urban Assisted Living 16th International Conference, ICOST 2018 ProceedingsEditors
M Mokhtari, B Abdulrazak and H AloulouPagination
179-188ISSN
0302-9743Department/School
School of Information and Communication TechnologyPublisher
Springer OpenPlace of publication
SwitzerlandEvent title
ICOST 2018: International Conference on Smart Homes and Health TelematicsEvent Venue
SingaporeDate of Event (Start Date)
2018-07-10Date of Event (End Date)
2018-07-12Rights statement
Copyright 2018 SpringerRepository Status
- Restricted