Semantic assessment of smart healthcare ontology

Tiwari, Sanju; Abraham, Ajith

doi:10.1108/ijwis-05-2020-0027

Cited by 21 publications

(7 citation statements)

References 29 publications

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“…The tool implemented is capable of a limited number of metrics but incorporation with other existing tools, e.g., Luzzu [3] and RDFUnit [6], can support the expansion of quality assessment. An integrated assessment approach performed by Sanju et al [9] is also promising to detect additional interoperability problems but inconsistency of performance among different assessment tools should be addressed. True machine readability of ontologies, concepts and classes is key to supporting reasoning over data and establishing FAIR linkable data.…”

Section: Discussionmentioning

confidence: 99%

Assessing Resolvability and Consistency in OBO Foundry Ontologies: Pilot Study

Zhang

Benis

Cornet

2021

Applying the FAIR Principles to Accelerate Health Research in Europe in the Post COVID-19 Era

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Ontologies listed in the OBO Foundry are often regarded as reliable choices to be reused but ontology interoperability of them remains unknown. This study evaluated the resolvability of URIs and consistency of axioms in the OBO Foundry library, BFO ontology, and CIDO ontology. All had nonresolvable URIs, but the OBO library and the CIDO had additional interoperability issues regarding the use of incorrect prefixes, mixing up with ontologies, and inconsistency in the use of property. These detected issues reflected the real-world common problems that were not significant from human beings’ point of view but hindered the machine-processability of ontologies. The assessment performed in this study was automated and enables scale-up against more metrics over more ontologies, which remains future work.

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Section: Discussionmentioning

confidence: 99%

Assessing Resolvability and Consistency in OBO Foundry Ontologies: Pilot Study

Zhang

Benis

Cornet

2021

Applying the FAIR Principles to Accelerate Health Research in Europe in the Post COVID-19 Era

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“…Sondes et al (2019) developed an IoTbased healthcare monitoring system utilizing ontology for semantic interoperability. Tiwari and Abraham (2020) introduced the Smart Healthcare Ontology (SHCO), extracting healthcare knowledge for improved healthcare monitoring systems. Shishehchi and Banihashem (2021) and Banihashem and Shishehchi (2022) exploited SWTs for knowledge acquisition in the diagnosis of immune thrombocytopenia and fatty liver diseases.…”

Section: Literature Reviewmentioning

confidence: 99%

An ontology-driven model for hospital equipment maintenance management: a case study

Titah,

Bouchaala

2024

JQME

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Purpose This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.Design/methodology/approach The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.Findings Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.Originality/value An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

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“…By using agile test-driven development (TDD) those defects can be effectively reduced [106]. TDD has also been used to asses smart healthcare ontologies, a technology which deals with healthcare information and IoT devices [107]. Patient management and engagement of chronic diseases with quality and usable mobile apps: quality and usability are two main factors to engage patients to use healthcare software [61,62], especially in case of mobile applications [63].…”

Section: Thematic Analysismentioning

confidence: 99%

Section: Thematic Analysismentioning

confidence: 99%

Agile Software Development in Healthcare: A Synthetic Scoping Review

Kokol

2022

Applied Sciences

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Even though software can be found everywhere, software development has encountered many problems, resulting in the emergence of new alternative development paradigms. Among them, agile approaches are the most popular. While much research has been published about agile software development (ASD) in general, there is a lack of documented knowledge about its use in healthcare. Consequently, it is not clear how ASD is used in healthcare, how it performs, and what the reasons are for not using it. To fill this gap, we performed a quantitative and qualitative knowledge synthesis of the research literature harvested from Scopus and Web of Science databases, employing the triangulation of bibliometrics and thematic analysis to answer the research question What is state of the art in using ASD in the healthcare sector? Results show that the research literature production trend is positive. The most productive countries are leading software development countries: the United States, China, the United Kingdom, Canada, and Germany. The research is mainly published in health informatics source titles. It is focused on improving the software process, quality of healthcare software, reduction of development resources, and general improvement of healthcare delivery. More research has to be done on scaling agile approaches to large-scale healthcare software development projects. Despite barriers, ASD can improve software development in healthcare settings and strengthen cooperation between healthcare and software development professionals. This could result in more successful digital health transformation and consequently more equitable access to expert-level healthcare, even on a global level.

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Semantic assessment of smart healthcare ontology

Cited by 21 publications

References 29 publications

Assessing Resolvability and Consistency in OBO Foundry Ontologies: Pilot Study

Assessing Resolvability and Consistency in OBO Foundry Ontologies: Pilot Study

An ontology-driven model for hospital equipment maintenance management: a case study

Agile Software Development in Healthcare: A Synthetic Scoping Review

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