Semantic Models in IoT and eHealth Applications

Front Cover
Semantic Models in IoT and eHealth Applications
Copyright
Contents
Contributors
Acknowledgments
1 Semantic modeling for healthcare applications: an introduction
	1.1 Introduction
	1.2 Literature review
	1.3 Background
		1.3.1 Semantic web and terminology
		1.3.2 Web-of-Things
		1.3.3 Semantic Web-of-Things
		1.3.4 IoT-based semantic models
			1.3.4.1 General-purpose IoT semantic models
				SSN/SOSA
				SAREF ontology
				Time
				QUDT
			1.3.4.2 Domain-specific IoT-based semantic models
	1.4 Semantic modeling of data
		1.4.1 Semantic annotation
		1.4.2 Semantic linking
			1.4.2.1 Construction of a semantic model
		1.4.3 Semantic representation
	1.5 Conclusions
	References
2 Role of IoT and semantics in e-Health
	2.1 Introduction
	2.2 Internet of Things in the healthcare industry
		2.2.1 Characteristics of IoT ontology and challenges in e-Health
		2.2.2 Characteristics of IoT in the healthcare industry
		2.2.3 Challenges of the IoT in e-Health
	2.3 Middleware architectures for the IoT in e-Health
		2.3.1 An overview of IoT middleware solutions
		2.3.2 Middleware solutions in healthcare
	2.4 Semantic interoperability of objects in e-Health
	2.5 Interoperability in healthcare
		2.5.1 Interoperability levels
		2.5.2 Turnista\'s model
		2.5.3 Semantic web
		2.5.4 OpenEHR archetype
	2.6 Conclusion
	References
3 Evaluation and visualization of healthcare semantic models
	3.1 Introduction and motivation
	3.2 Role of visualization: background
		3.2.1 Visualization concept and its cognitive capacity
		3.2.2 Visualization in ICT, healthcare, and biomedical sectors
		3.2.3 Basics of visualization
		3.2.4 Visualization of semantic models
		3.2.5 Visualization of ontology and semantic model in healthcare and (bio)medical sectors
			3.2.5.1 Task-dependency of visualization
			3.2.5.2 Visualization of semantic models: classification by the visualization technique
	3.3 Requirement of evaluation
		3.3.1 Taxonomy of the evaluation
			3.3.1.1 Recommenders
			3.3.1.2 Ontology evaluation tool
			3.3.1.3 Ontology visualization
			3.3.1.4 Briefly on other approaches
			3.3.1.5 Feature-based evaluation of ontology visualization tools
			3.3.1.6 Taxonomy of evaluation techniques
		3.3.2 How to make a choice of a visualization tool
	3.4 Discussion
	3.5 Conclusion
	Acknowledgments
	References
4 Role of connected objects in healthcare semantic models
	4.1 Introduction
	4.2 The EHR ecosystem
		4.2.1 OpenEHR
		4.2.2 Health level seven international (HL7)
		4.2.3 ISO 13606
		4.2.4 Semantic models in healthcare
	4.3 Connected objects in healthcare
		4.3.1 Internet of things
		4.3.2 Semantic sensor network
		4.3.3 M2M
		4.3.4 oneM2M
		4.3.5 Smart appliances reference ontology
	4.4 Semantic-based connected objects in e-Health
		4.4.1 Semantic integration of IoT and EHR systems
		4.4.2 Data-centric e-Health perspective
			4.4.2.1 Modeling
			4.4.2.2 Preprocessing
			4.4.2.3 Persistence
	4.5 Concluding remarks
	References
5 The security and privacy aspects in semantic web enabled IoT-based healthcare information systems
	5.1 Introduction and motivation
	5.2 Security and privacy requirements in IoT
		5.2.1 Security and privacy challenges in IoT
		5.2.2 IoT security attacks and threats
	5.3 Security and privacy concerns in IoT-based healthcare systems
	5.4 Semantic web based solutions for security and privacy
	5.5 Semantic web based solutions for the security and privacy aspects in the IoT ecosystem
		5.5.1 Security oriented solutions
		5.5.2 Privacy oriented solutions
	5.6 Challenges and future directions for the security and privacy concerns in IoT-based healthcare systems
	5.7 Conclusions
	References
6 Knowledge-based system as a context-aware approach for the Internet of medical connected objects
	6.1 Introduction
	6.2 Knowledge-based system in health
	6.3 Context modeling using knowledge graphs
	6.4 Knowledge graphs
	6.5 Integrated domain model
	6.6 Discussion and conclusions
	References
7 Toward a knowledge graph for medical diagnosis: issues and usage scenarios
	7.1 Introduction
	7.2 Related work
	7.3 A knowledge graph for medical diagnosis
	7.4 Issues for ontology alignment
		7.4.1 Alignment between DOID and SYMP ontologies
		7.4.2 Issues for ICD-10 and DOID-SYMP alignment
	7.5 Usage scenarios for the medical diagnosis knowledge graph
		7.5.1 Electronic health records interoperability
		7.5.2 Automatic reasoning in telemedicine
		7.5.3 Medical insurance management
	7.6 Conclusion
	References
8 A naturopathy knowledge graph and recommendation system to boost the immune system
	8.1 Introduction
	8.2 Related work: food knowledge graphs and recommendation systems
		8.2.1 Food knowledge graphs: ontologies and data sets
		8.2.2 Food recommender systems
		8.2.3 Food information extraction with natural language processing: named-entity recognition
		8.2.4 Shortcomings of the literature study
	8.3 Naturopathy knowledge graph and recommendation system to boost immune system: knowledge-based immune system suggestion
		8.3.1 Collecting food ontologies: LOV4IoT-food ontology catalog
		8.3.2 Naturopathy knowledge graph: extracting and integrating food ontologies and data sets
		8.3.3 Knowledge-based immune system suggestion: ontology-based food recommendation to boost the immune system
		8.3.4 Evaluation
	8.4 Conclusion and future work
	8.5 Disclaimer
	8.A Demonstrators
	References
9 SAREF4EHAW-compliant knowledge discovery and reasoning for IoT-based preventive health and well-being
	9.1 Introduction
	9.2 Related work: ontology-based IoT project catalog for health
		9.2.1 Ontology-based IoT project catalog for health with LOV4IoT-health
		9.2.2 Standards: ISO and ETSI SmartM2M
			9.2.2.1 ETSI SmartM2M SAREF4EHAW for e-Health/Aging-well
			9.2.2.2 ISO 13606-5:2010 health informatics – electronic health record communication standards
		9.2.3 Health knowledge graphs
	9.3 Knowledge discovery and reasoning for preventive health and well-being
		9.3.1 ETSI SmartM2M SAREF-compliant semantic sensor health dictionary
		9.3.2 Ontology visualization for preventive health and well being
		9.3.3 Semi-automatic knowledge extraction from preventive health and well being ontologies
			9.3.3.1 Extracting specific terms from ontology code
			9.3.3.2 Extracting knowledge from scientific publications
			9.3.3.3 Usage of semiautomatic extraction within reasoning demonstrators
		9.3.4 Knowledge discovery and reasoning for preventive health and well-being (S-LOR health)
		9.3.5 Keeping track of provenance metadata
	9.4 End-to-end knowledge-based health and well-being use cases
	9.5 Key contributions and lessons learned
	9.6 Conclusion and future work
	Acknowledgments
	9.A IoT-based ontologies for health
		9.A.1 Ambient assisted-living (AAL)/ remote monitoring for health ontologies using IoT technologies
		9.A.2 Disease-related ontologies
			9.A.2.1 Cardiology-related ontologies
			9.A.2.2 Diabetes and diet-related ontologies
			9.A.2.3 Dementia models, ontologies or KGs: Parkinson\'s, Alzheimer\'s, etc.
		9.A.3 Electronic Health Records (EHR) ontologies
		9.A.4 Wearable ontologies
		9.A.5 Ontologies from European projects: ACTIVAGE and HEARTFAID
		9.A.6 Other ontologies
	References
10 Reasoning over personalized healthcare knowledge graph: a case study of patients with allergies and symptoms
	10.1 Introduction
	10.2 Related work
	10.3 A reasoner for personalized health knowledge graph
	10.4 Implementation, results, and evaluation
		10.4.1 Implementation
		10.4.2 KAO ontology evaluation
	10.5 Discussions and extensions for future work
	10.6 Conclusion
	Acknowledgments
	10.A Listings: code example
	10.B Tutorials: SPARQL queries and End-to-End Scenarios
	References
	Web references
11 Integrated context-aware ontology for MNCH decision support
	11.1 Introduction
	11.2 Related works
	11.3 Preposition-enabled spatial ontology: PeSONT
		11.3.1 Concept extraction
		11.3.2 Term formalization
		11.3.3 Location visualization
	11.4 PeSONT documentation
	11.5 Discussion
	11.6 Conclusions
	Acknowledgments
	References
12 IntelliOntoRec: a knowledge infused semiautomatic approach for ontology formulation in healthcare and medical science
	12.1 Introduction
	12.2 Related works
	12.3 Proposed model
		12.3.1 Phase 1
		12.3.2 Transformer architecture
		12.3.3 Phase 2
		12.3.4 Phase 3
	12.4 Implementation
	12.5 Results
	12.6 Conclusion
	References
Index
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