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Semantic Models in IoT and eHealth Applications explores the key role of semantic web modeling in eHealth technologies, including remote monitoring, mobile health, cloud data and biomedical ontologies. The book explores different challenges and issues through the lens of various case studies of healthcare systems currently adopting these technologies. Chapters introduce the concepts of semantic interoperability within a healthcare model setting and explore how semantic representation is key to classifying, analyzing and understanding the massive amounts of biomedical data being generated by connected medical devices. Continuous health monitoring is a strong solution which can provide eHealth services to a community through the use of IoT-based devices that collect sensor data for efficient health diagnosis, monitoring and treatment. All of this collected data needs to be represented in the form of ontologies which are considered the cornerstone of the Semantic Web for knowledge sharing, information integration and information extraction.
Semantic modeling for healthcare applications an introduction
Role of IoT and semantics in e-Health
Evaluation and visualization of healthcare semantic models
Role of connected objects in healthcare semantic models
The security and privacy aspects in semantic web enabled IoT-based healthcare information systems
Knowledge-based system as a context-aware approach for the Internet of medical connected objects
Toward a knowledge graph for medical diagnosis issues and usage scenarios
A naturopathy knowledge graph and recommendation system to boost the immune system
SAREF4EHAW-compliant knowledge discovery and reasoning for IoT-based preventive health and well-being
Reasoning over personalized healthcare knowledge graph a case study of patients with allergies and symptoms
Integrated context-aware ontology for MNCH decision support
IntelliOntoRec a knowledge infused semiautomatic approach for ontology formulation in healthcare and medical science