Semantic Models in IoT and eHealth Applications

Herausgeber: Ortiz Rodriguez, Fernando; Tiwari, Sanju; Jabbar, M. A.

• Broschiertes Buch

Produktbeschreibung

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.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Intelligent Data-Centric Systems
• Verlag: Elsevier Science & Technology
• Seitenzahl: 290
• Erscheinungstermin: 23. September 2022
• Englisch
• Abmessung: 191mm x 237mm x 24mm
• Gewicht: 620g
• ISBN-13: 9780323917735
• ISBN-10: 0323917739
• Artikelnr.: 63120825

Inhaltsangabe

1. Semantic Modelling for Healthcare Applications: An Introduction
2. Role of IoT and semantics in Ehealth
3. Evaluation and Visualization of Healthcare Semantic Models
4. Role of Connected objects in Healthcare Semantic Models
5. The Security and Privacy Aspects in Semantic Web enabled IoT based
Healthcare Information Systems
6. Knowledge-based System as a Context-aware Approach for the Internet of
Medical Connected Objects
7. Towards a Knowledge Graph for Medical Diagnosis: Issues and Usage
Scenarios
8. A Naturopathy Knowledge Graph and Recommendation System to Boost the
Immune System
9. SAREF4EHAW-Compliant Knowledge Discovery and Reasoning \\for IoT-based
Preventive Healthcare and Well-Being
10. Reasoning Over Personalized Healthcare Knowledge Graph: A Case Study of
Patients with Allergies and Symptoms
11. Integrated Context-aware Ontology for MNCH Decision Support
12.  IntelliOntoRec: A Knowledge Infused Semiautomatic Approach for
Ontology Formulation in Healthcare and Medical Science