Semantic Web for Effective Healthcare Systems

Semantic Web for Effective Healthcare Systems

by Vishal Jain, Jyotir Moy Chatterjee, Ankita Bansal, Abha Jain
Released December 2021
Publisher(s): Wiley-Scrivener
ISBN: 9781119762294

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Book description

SEMANTIC WEB FOR EFFECTIVE HEALTHCARE SYSTEMS

The book summarizes the trends and current research advances in web semantics, delineating the existing tools, techniques, methodologies, and research solutions

Semantic Web technologies have the opportunity to transform the way healthcare providers utilize technology to gain insights and knowledge from their data and make treatment decisions. Both Big Data and Semantic Web technologies can complement each other to address the challenges and add intelligence to healthcare management systems.

The aim of this book is to analyze the current status on how the semantic web is used to solve health data integration and interoperability problems, and how it provides advanced data linking capabilities that can improve search and retrieval of medical data. Chapters analyze the tools and approaches to semantic health data analysis and knowledge discovery. The book discusses the role of semantic technologies in extracting and transforming healthcare data before storing it in repositories. It also discusses different approaches for integrating heterogeneous healthcare data.

This innovative book offers:

  • The first of its kind and highlights only the ontology driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems;
  • Presents a comprehensive examination of the emerging research in areas of the semantic web;
  • Discusses studies on new research areas including ontological engineering, semantic annotation and semantic sentiment analysis;
  • Helps readers understand key concepts in semantic web applications for the biomedical engineering and healthcare fields;
  • Includes coverage of key application areas of the semantic web.

Audience: Researchers and graduate students in computer science, biomedical engineering, electronic and software engineering, as well as industry scientific researchers, clinicians, and systems managers in biomedical fields.

Table of contents

  1. Cover
  2. Title page
  3. Copyright
  4. Preface
  5. Acknowledgment
  6. 1 An Ontology-Based Contextual Data Modeling for Process Improvement in Healthcare
    1. 1.1 Introduction
    2. 1.2 Related Work
    3. 1.3 Motivation
    4. 1.4 Feature Extraction
    5. 1.5 Ontology Development
    6. 1.6 Dataset Description
    7. 1.7 Results and Discussions
    8. 1.8 Applications
    9. 1.9 Conclusion
    10. 1.10 Future Work
    11. References
  7. 2 Semantic Web for Effective Healthcare Systems: Impact and Challenges
    1. 2.1 Introduction
    2. 2.2 Overview of the Website in Healthcare
    3. 2.3 Data and Database
    4. 2.4 Big Data and Database Security and Protection
    5. References
  8. 3 Ontology-Based System for Patient Monitoring
    1. 3.1 Introduction
    2. 3.2 Literature Review
    3. 3.3 Architectural Design
    4. 3.4 Experimental Results
    5. 3.5 Conclusion and Future Enhancements
    6. References
  9. 4 Semantic Web Solutions for Improvised Search in Healthcare Systems
    1. 4.1 Introduction
    2. 4.2 Background
    3. 4.3 Searching Techniques in Healthcare Systems
    4. 4.4 Emerging Technologies/Resources in Health Sector
    5. 4.5 Conclusion
    6. References
  10. 5 Actionable Content Discovery for Healthcare
    1. 5.1 Introduction
    2. 5.2 Actionable Content
    3. 5.3 Health Analytics
    4. 5.4 Ontologies and Actionable Content
    5. 5.5 General Architecture for the Discovery of Actionable Content for Healthcare Domain
    6. 5.6 Conclusion
    7. References
  11. 6 Intelligent Agent System Using Medicine Ontology
    1. 6.1 Introduction to Semantic Search
    2. 6.2 Sematic Search
    3. 6.3 Structural Pattern of Semantic Search
    4. 6.4 Implementation of Reasoners
    5. 6.5 Implementation and Results
    6. 6.6 Conclusion and Future Prospective
    7. References
  12. 7 Ontology-Based System for Robotic Surgery—A Historical Analysis
    1. 7.1 Historical Discourse of Surgical Robots
    2. 7.2 The Necessity for Surgical Robots
    3. 7.3 Ontological Evolution of Robotic Surgical Procedures in Various Domains
    4. 7.4 Inferences Drawn From the Table
    5. 7.5 Transoral Robotic Surgery
    6. 7.6 Pancreatoduodenectomy
    7. 7.7 Robotic Mitral Valve Surgery
    8. 7.8 Rectal Tumor Surgery
    9. 7.9 Robotic Lung Cancer Surgery
    10. 7.10 Robotic Surgery in Gynecology
    11. 7.11 Robotic Radical Prostatectomy
    12. 7.12 Conclusion
    13. 7.13 Future Work
    14. References
  13. 8 IoT-Enabled Effective Healthcare Monitoring System Using Semantic Web
    1. 8.1 Introduction
    2. 8.2 Literature Review
    3. 8.3 Phases of IoT-Based Healthcare
    4. 8.4 IoT-Based Healthcare Architecture
    5. 8.5 IoT-Based Sensors for Health Monitoring
    6. 8.6 IoT Applications in Healthcare
    7. 8.7 Semantic Web, Ontology, and Its Usage in Healthcare Sector
    8. 8.8 Semantic Web-Based IoT Healthcare
    9. 8.9 Challenges of IoT in Healthcare Industry
    10. 8.10 Conclusion
    11. References
  14. 9 Precision Medicine in the Context of Ontology
    1. 9.1 Introduction
    2. 9.2 The Rationale Behind Data
    3. 9.3 Data Standards for Interoperability
    4. 9.4 The Evolution of Ontology
    5. 9.5 Ontologies and Classifying Disorders
    6. 9.6 Phenotypic Ontology of Humans in Rare Disorders
    7. 9.7 Annotations and Ontology Integration
    8. 9.8 Precision Annotation and Integration
    9. 9.9 Ontology in the Contexts of Gene Identification Research
    10. 9.10 Personalizing Care for Chronic Illness
    11. 9.11 Roadblocks Toward Precision Medicine
    12. 9.12 Future Perspectives
    13. 9.13 Conclusion
    14. References
  15. 10 A Knowledgebase Model Using RDF Knowledge Graph for Clinical Decision Support Systems
    1. 10.1 Introduction
    2. 10.2 Relational Database to Graph Database
    3. 10.3 RDF
    4. 10.4 Knowledgebase Systems and Knowledge Graphs
    5. 10.5 Knowledge Base for CDSS
    6. 10.6 Discussion for Further Research and Development
    7. 10.7 Conclusion
    8. References
  16. 11 Medical Data Supervised Learning Ontologies for Accurate Data Analysis
    1. 11.1 Introduction
    2. 11.2 Ontology of Biomedicine
    3. 11.3 Supervised Learning
    4. 11.4 AQ21 Rule in Machine Learning
    5. 11.5 Unified Medical Systems
    6. 11.6 Performance Analysis
    7. 11.7 Conclusion
    8. References
  17. 12 Rare Disease Diagnosis as Information Retrieval Task
    1. 12.1 Introduction
    2. 12.2 Definition
    3. 12.3 Characteristics of Rare Diseases (RDs)
    4. 12.4 Types of Rare Diseases
    5. 12.5 A Brief Classification
    6. 12.6 Rare Disease Databases and Online Resources
    7. 12.7 Information Retrieval of Rare Diseases Through a Web Search and Other Methods
    8. 12.8 Tips and Tricks for Information Retrieval
    9. 12.9 Research on Rare Disease Throughout the World
    10. 12.10 Conclusion
    11. References
  18. 13 Atypical Point of View on Semantic Computing in Healthcare
    1. 13.1 Introduction
    2. 13.2 Mind the Language
    3. 13.3 Semantic Analytics and Cognitive Computing: Recent Trends
    4. 13.4 Semantics-Powered Healthcare SOS Engineering
    5. 13.5 Conclusion
    6. References
  19. 14 Using Artificial Intelligence to Help COVID-19 Patients
    1. 14.1 Introduction
    2. 14.2 Method
    3. 14.3 Results
    4. 14.4 Discussion
    5. 14.5 Conclusion
    6. Acknowledgment
    7. References
  20. Index
  21. End User License Agreement

Product information

  • Title: Semantic Web for Effective Healthcare Systems
  • Author(s): Vishal Jain, Jyotir Moy Chatterjee, Ankita Bansal, Abha Jain
  • Release date: December 2021
  • Publisher(s): Wiley-Scrivener
  • ISBN: 9781119762294