Semantic Models in IoT and eHealth Applications
- 1st Edition - September 17, 2022
- Imprint: Academic Press
- Editors: Sanju Tiwari, Fernando Ortiz Rodriguez, M.A. Jabbar
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 1 7 7 3 - 5
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 7 2 2 6 - 0
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… Read more
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Request a sales quoteSemantic 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.
- Presents comprehensive coverage of advances in the application of semantic web in the field of eHealth
- Explores different challenges and issues through various case studies of healthcare systems that are adopting semantic web technologies
- Covers applications across a range of eHealth technologies, including remote monitoring and mobile health
Researchers, professionals, and graduate students in computer science & engineering; bioinformatics; biomedical engineering
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Acknowledgments
- Chapter 1: Semantic modeling for healthcare applications: an introduction
- Abstract
- 1.1. Introduction
- 1.2. Literature review
- 1.3. Background
- 1.4. Semantic modeling of data
- 1.5. Conclusions
- References
- Chapter 2: Role of IoT and semantics in e-Health
- Abstract
- 2.1. Introduction
- 2.2. Internet of Things in the healthcare industry
- 2.3. Middleware architectures for the IoT in e-Health
- 2.4. Semantic interoperability of objects in e-Health
- 2.5. Interoperability in healthcare
- 2.6. Conclusion
- References
- Chapter 3: Evaluation and visualization of healthcare semantic models
- Abstract
- Acknowledgements
- 3.1. Introduction and motivation
- 3.2. Role of visualization: background
- 3.3. Requirement of evaluation
- 3.4. Discussion
- 3.5. Conclusion
- References
- Chapter 4: Role of connected objects in healthcare semantic models
- Abstract
- 4.1. Introduction
- 4.2. The EHR ecosystem
- 4.3. Connected objects in healthcare
- 4.4. Semantic-based connected objects in e-Health
- 4.5. Concluding remarks
- References
- Chapter 5: The security and privacy aspects in semantic web enabled IoT-based healthcare information systems
- Abstract
- 5.1. Introduction and motivation
- 5.2. Security and privacy requirements in IoT
- 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
- 5.6. Challenges and future directions for the security and privacy concerns in IoT-based healthcare systems
- 5.7. Conclusions
- References
- Chapter 6: Knowledge-based system as a context-aware approach for the Internet of medical connected objects
- Abstract
- 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
- Chapter 7: Toward a knowledge graph for medical diagnosis: issues and usage scenarios
- Abstract
- 7.1. Introduction
- 7.2. Related work
- 7.3. A knowledge graph for medical diagnosis
- 7.4. Issues for ontology alignment
- 7.5. Usage scenarios for the medical diagnosis knowledge graph
- 7.6. Conclusion
- References
- Chapter 8: A naturopathy knowledge graph and recommendation system to boost the immune system
- Abstract
- 8.1. Introduction
- 8.2. Related work: food knowledge graphs and recommendation systems
- 8.3. Naturopathy knowledge graph and recommendation system to boost immune system: knowledge-based immune system suggestion
- 8.4. Conclusion and future work
- 8.5. Disclaimer
- Appendix 8.A. Demonstrators
- References
- Chapter 9: SAREF4EHAW-compliant knowledge discovery and reasoning for IoT-based preventive health and well-being
- Abstract
- Acknowledgements
- 9.1. Introduction
- 9.2. Related work: ontology-based IoT project catalog for health
- 9.3. Knowledge discovery and reasoning for preventive health and well-being
- 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
- Appendix 9.A. IoT-based ontologies for health
- References
- Chapter 10: Reasoning over personalized healthcare knowledge graph: a case study of patients with allergies and symptoms
- Abstract
- Acknowledgements
- 10.1. Introduction
- 10.2. Related work
- 10.3. A reasoner for personalized health knowledge graph
- 10.4. Implementation, results, and evaluation
- 10.5. Discussions and extensions for future work
- 10.6. Conclusion
- Appendix 10.A. Listings: code example
- Appendix 10.B. Tutorials: SPARQL queries and End-to-End Scenarios
- References
- Web references
- Chapter 11: Integrated context-aware ontology for MNCH decision support
- Abstract
- Acknowledgements
- 11.1. Introduction
- 11.2. Related works
- 11.3. Preposition-enabled spatial ontology: PeSONT
- 11.4. PeSONT documentation
- 11.5. Discussion
- 11.6. Conclusions
- References
- Chapter 12: IntelliOntoRec: a knowledge infused semiautomatic approach for ontology formulation in healthcare and medical science
- Abstract
- 12.1. Introduction
- 12.2. Related works
- 12.3. Proposed model
- 12.4. Implementation
- 12.5. Results
- 12.6. Conclusion
- References
- Index
- Edition: 1
- Published: September 17, 2022
- Imprint: Academic Press
- No. of pages: 290
- Language: English
- Paperback ISBN: 9780323917735
- eBook ISBN: 9780323972260
ST
Sanju Tiwari
Dr. Sanju Tiwari is a Professor at Sharda University, Greater Noida, India; as well as CEO and Founder of ShodhGuru Research Labs, India. She is DAAD Post-Doc-Net AI Fellow for 2021 and visited different German Universities (Leibniz University Hannover, Leipzig University, Leipzig, Lubeck University and Luephana University Luneburg) in June 2022 under this DAAD fellowship. She is a Mentor of Google Summer of Code (GSoC 2022-23) at DBpedia and a member of InfAI, Leipzig University, Germany. She is also working as a curator of ORKG Grant Program, at TIB Hannover, Germany. She also appointed as Ph.D. Co-Supervisor at Rai University, Gujarat, India. She has worked as a Post-Doctoral Researcher in Ontology Engineering Group, Universidad Politecnica De Madrid, Spain. Prior to this, she worked as a Research Associate for a sponsored research project “Intelligent Real-time Situation Awareness and Decision Support System for Indian Defence” funded by DRDO, New Delhi, India. Her current research interests include, Ontology Engineering, Knowledge Graphs, Linked Data, Artificial Intelligence. She has to-date published >100 research papers and 6 Scopus indexed Books. She has edited books based on Semantic Web in IoT, Personal Knowledge Graphs and Semantic AI in Knowledge Graphs.
Affiliations and expertise
Sharda University, Department of Computer Science & Applications, Greater Noida, IndiaFO
Fernando Ortiz Rodriguez
Dr. Rodriguez is a Full Professor and is the Social Science Research Center Director at Tamaulipas Autonomous University. Before this, he was the Executive Director at the International Institute of Studies (IIES); he created the First Business School in Tamaulipas, Mexico, and before this, he was the Information Technology Manager at Emerson Electric, where he developed more than 40 software's, some of them used globally in Emerson and achieved technology convergence implementing the first efforts on IoT and Industry 4.0
He is a member of National Systems Researchers (SNI) of the National Council of Science and Technology (CONACYT). He published several articles, book chapters, and books in prestigious editorials. He has guided more than fifteen bachelor's and five postgraduate theses. Additionally, he has more than ten software patents. He received a Latin-American award (U-Gob) for implementing and developing software to help with Covid-19 diagnosis in Mexico.
Affiliations and expertise
Full Professor, Autonomous University of Tamaulipas, Victoria, Tamaulipas, MexicoMJ
M.A. Jabbar
Dr. Jabbar is Professor and Head of the Department of Computer Science and Engineering, Vardhaman College of Engineering, Hyderabad, Telangana, India. He obtained his PhD from JNTUH, Hyderabad, and Telangana, India. He has been teaching for more than 20 years. His research interests include Artificial Intelligence, Big Data Analytics, Bioinformatics, Cyber Security, Machine Learning, Attack Graphs, and Intrusion Detection Systems. He has published more than 57 papers in various journals and conferences. He published 5 patents in machine learning and allied areas and one book, Heart Disease Data Classification using Data Mining Techniques (LAP LAMBERT Academic, 2019). He served as a technical committee member for more than 70 international conferences. He is Guest Editor for The Fusion of Internet of Things, AI, and Cloud Computing In Health Care: Opportunities and Challenges (Springer) Series, and Deep Learning in Biomedical and Health Informatics: Current Applications and Possibilities (CRC Press); Guest Editor for Emerging Technologies and Applications for a Smart and Sustainable World (Bentham Science); Guest editor for Machine Learning Methods for Signal, Image and Speech Processing (River Publishing). He is a senior member of IEEE, and Lifetime member of the Computer Society of India (CSI) and the Indian Science Congress Association (ISCA). He is chair of the IEEE CS chapter Hyderabad Section. He has also served as a member of the Machine Intelligence Laboratory, USA (MIRLABS) and USERN, Iran, and Asia Pacific Institute of Science and Engineering (APISE) Hong Kong.
Affiliations and expertise
Professor and Head of the Department of Computer Science and Engineering, Vardhaman College of Engineering, Hyderabad, Telangana, IndiaRead Semantic Models in IoT and eHealth Applications on ScienceDirect