A Systematic Literature Review on Ontology Based Context Management System

Subbaraj, Rajarajeswari; Venkatraman, Neelanarayanan

doi:10.1007/978-3-319-13731-5_66

Cited by 5 publications

(2 citation statements)

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“…Evaluating and understanding the technical factors involved in building effective ontology-based CDSSs can pave the way for more efficient system design and selection. Several systematic literature reviews have been conducted on implementing ontologies on information systems and technology [18][19][20][21][22]. However, as far as we know, no systematic review has specifically reviewed the implementation of ontologies in guideline-based clinical decision support systems.…”

Section: Introductionmentioning

confidence: 99%

How are ontologies implemented to represent clinical practice guidelines in clinical decision support systems: protocol for a systematic review

et al. 2022

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Background Clinical practice guidelines are statements which are based on the best available evidence, and their goal is to improve the quality of patient care. Integrating clinical practice guidelines into computer systems can help physicians reduce medical errors and help them to have the best possible practice. Guideline-based clinical decision support systems play a significant role in supporting physicians in their decisions. Meantime, system errors are the most critical concerns in designing decision support systems that can affect their performance and efficacy. A well-developed ontology can be helpful in this matter. The proposed systematic review will specify the methods, components, language of rules, and evaluation methods of current ontology-driven guideline-based clinical decision support systems. Methods This review will identify literature through searching MEDLINE (via Ovid), PubMed, EMBASE, Cochrane Library, CINAHL, ScienceDirect, IEEEXplore, and ACM Digital Library. Gray literature, reference lists, and citing articles of the included studies will be searched. The quality of the included studies will be assessed by the mixed methods appraisal tool (MMAT-version 2018). At least two independent reviewers will perform the screening, quality assessment, and data extraction. A third reviewer will resolve any disagreements. Proper data analysis will be performed based on the type of system and ontology engineering evaluation data. Discussion The study will provide evidence regarding applying ontologies in guideline-based clinical decision support systems. The findings of this systematic review will be a guide for decision support system designers and developers, technologists, system providers, policymakers, and stakeholders. Ontology builders can use the information in this review to build well-structured ontologies for personalized medicine. Systematic review registration PROSPERO CRD42018106501

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Section: Introductionmentioning

confidence: 99%

How are ontologies implemented to represent clinical practice guidelines in clinical decision support systems: protocol for a systematic review

et al. 2022

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“…Ontology models are the most ground approach for knowledge modelling (Subbaraj and Venkatraman, 2015;Monteiro et al, 2014), as they provide a common terminology which is essential to enable cooperation among self-managed entities (Staab and Studer, 2013) and that necessity of coordination is a point where all autonomic approaches agree. That cooperation grounds in the idea that autonomic management entities need to cooperate among them to achieve a desired goal, but this is not a new idea in the agent engineering (Wooldridge, 2009) field where the concept of agent grounds exactly in the same idea.…”

Section: Related Workmentioning

confidence: 99%