Ontology-based information retrieval for healthcare systems. (2020)

• Record Type: Book
• Further Information: Note: Edited by Vishal Jain, Ritika Wason, Jyotir Moy Chatterjee, Dac-Nhuong Le.
• Editors: Jain, Vishal, 1983-; Wason, Ritika, 1982-; Chatterjee, Jyotir Moy; Le, Dac-Nhuong, 1983-
• Contents: Preface xix Acknowledgment xxiii 1 Role of Ontology in Health Care 1; Sonia Singla 1.1 Introduction 2 1.2 Ontology in Diabetes 3 1.2.1 Ontology Process 4 1.2.2 Impediments of the Present Investigation 5 1.3 Role of Ontology in Cardiovascular Diseases 6 1.4 Role of Ontology in Parkinson Diseases 8 1.4.1 The Spread of Disease With Age and Onset of Disease 10 1.4.2 Cost of PD for Health Care, Household 11 1.4.3 Treatment and Medicines 11 1.5 Role of Ontology in Depression 13 1.6 Conclusion 15 1.7 Future Scope 15 References 15 2 A Study on Basal Ganglia Circuit and Its Relation With Movement Disorders 19; Dinesh Bhatia 2.1 Introduction 19 2.2 Anatomy and Functioning of Basal Ganglia 21 2.2.1 The Striatum-Major Entrance to Basal Ganglia Circuitry 22 2.2.2 Direct and Indirect Striatofugal Projections 23 2.2.3 The STN: Another Entrance to Basal Ganglia Circuitry 25 2.3 Movement Disorders 26 2.3.1 Parkinson Disease 26 2.3.2 Dyskinetic Disorder 27 2.3.3 Dystonia 28 2.4 Effect of Basal Ganglia Dysfunctioning on Movement Disorders 29 2.5 Conclusion and Future Scope 31 References 31 3 Extraction of Significant Association Rules Using Pre- and Post-Mining Techniques—An Analysis 37; M. Nandhini and S. N. Sivanandam 3.1 Introduction 38 3.2 Background 39 3.2.1 Interestingness Measures 39 3.2.2 Pre-Mining Techniques 40 3.2.2.1 Candidate Set Reduction Schemes 40 3.2.2.2 Optimal Threshold Computation Schemes 41 3.2.2.3 Weight-Based Mining Schemes 42 3.2.3 Post-Mining Techniques 42 3.2.3.1 Rule Pruning Schemes 43 3.2.3.2 Schemes Using Knowledge Base 43 3.3 Methodology 44 3.3.1 Data Preprocessing 44 3.3.2 Pre-Mining 46 3.3.2.1 Pre-Mining Technique 1: Optimal Support and Confidence Threshold Value Computation Using PSO 46 3.3.2.2 Pre-Mining Technique 2: Attribute Weight Computation Using IG Measure 48 3.3.3 Association Rule Generation 50 3.3.3.1 ARM Preliminaries 50 3.3.3.2 WARM Preliminaries 52 3.3.4 Post-Mining 56 3.3.4.1 Filters 56 3.3.4.2 Operators 58 3.3.4.3 Rule Schemas 58 3.4 Experiments and Results 59 3.4.1 Parameter Settings for PSO-Based Pre-Mining Technique 60 3.4.2 Parameter Settings for PAW-Based Pre-Mining Technique 60 3.5 Conclusions 63 References 65 4 Ontology in Medicine as a Database Management System 69; Shobowale K. O. 4.1 Introduction 70 4.1.1 Ontology Engineering and Development Methodology 72 4.2 Literature Review on Medical Data Processing 72 4.3 Information on Medical Ontology 75 4.3.1 Types of Medical Ontology 75 4.3.2 Knowledge Representation 76 4.3.3 Methodology of Developing Medical Ontology 76 4.3.4 Medical Ontology Standards 77 4.4 Ontologies as a Knowledge-Based System 78 4.4.1 Domain Ontology in Medicine 79 4.4.2 Brief Introduction of Some Medical Standards 81 4.4.2.1 Medical Subject Headings (MeSH) 81 4.4.2.2 Medical Dictionary for Regulatory Activities (MedDRA) 81 4.4.2.3 Medical Entities Dictionary (MED) 81 4.4.3 Reusing Medical Ontology 82 4.4.4 Ontology Evaluation 85 4.5 Conclusion 86 4.6 Future Scope 86 References 87 5 Using IoT and Semantic Web Technologies for Healthcare and Medical Sector 91; Nikita Malik and Sanjay Kumar Malik 5.1 Introduction 92 5.1.1 Significance of Healthcare and Medical Sector and Its Digitization 92 5.1.2 e-Health and m-Health 92 5.1.3 Internet of Things and Its Use 94 5.1.4 Semantic Web and Its Technologies 96 5.2 Use of IoT in Healthcare and Medical Domain 98 5.2.1 Scope of IoT in Healthcare and Medical Sector 98 5.2.2 Benefits of IoT in Healthcare and Medical Systems 100 5.2.3 IoT Healthcare Challenges and Open Issues 100 5.3 Role of SWTs in Healthcare Services 101 5.3.1 Scope and Benefits of Incorporating Semantics in Healthcare 101 5.3.2 Ontologies and Datasets for Healthcare and Medical Domain 103 5.3.3 Challenges in the Use of SWTs in Healthcare Sector 104 5.4 Incorporating IoT and/or SWTs in Healthcare and Medical Sector 106 5.4.1 Proposed Architecture or Framework or Model 106 5.4.2 Access Mechanisms or Approaches 108 5.4.3 Applications or Systems 109 5.5 Healthcare Data Analytics Using Data Mining and Machine Learning 110 5.6 Conclusion 112 5.7 Future Work 113 References 113 6 An Ontological Model, Design, and Implementation of CSPF for Healthcare 117; Pooja Mohan 6.1 Introduction 117 6.2 Related Work 119 6.3 Mathematical Representation of CSPF Model 122 6.3.1 Basic Sets of CSPF Model 123 6.3.2 Conditional Contextual Security and Privacy Constraints 123 6.3.3 CSPF Model States CsetofStates 124 6.3.4 Permission Cpermission 124 6.3.5 Security Evaluation Function (SEFcontexts ) 124 6.3.6 Secure State 125 6.3.7 CSPF Model Operations 125 6.3.7.1 Administrative Operations 125 6.3.7.2 Users’ Operations 127 6.4 Ontological Model 127 6.4.1 Development of Class Hierarchy 127 6.4.1.1 Object Properties of Sensor Class 129 6.4.1.2 Data Properties 129 6.4.1.3 The Individuals 129 6.5 The Design of Context-Aware Security and Privacy Model for Wireless Sensor Network 129 6.6 Implementation 133 6.7 Analysis and Results 135 6.7.1 Inference Time/Latency/Query Response Time vs. No. of Policies 135 6.7.2 Average Inference Time vs. Contexts 136 6.8 Conclusion and Future Scope 137 References 138 7 Ontology-Based Query Retrieval Support for E-Health Implementation 143; Aatif Ahmad Khan and Sanjay Kumar Malik 7.1 Introduction 143 7.1.1 Health Care Record Management 144 7.1.1.1 Electronic Health Record 144 7.1.1.2 Electronic Medical Record 145 7.1.1.3 Picture Archiving and Communication System 145 7.1.1.4 Pharmacy Systems 145 7.1.2 Information Retrieval 145 7.1.3 Ontology 146 7.2 Ontology-Based Query Retrieval Support 146 7.3 E-Health 150 7.3.1 Objectives and Scope 150 7.3.2 Benefits of E-Health 151 7.3.3 E-Health Implementation 151 7.4 Ontology-Driven Information Retrieval for E-Health 154 7.4.1 Ontology for E-Heath Implementation 155 7.4.2 Frameworks for Information Retrieval Using Ontology for E-Health 157 7.4.3 Applications of Ontology-Driven Information Retrieval in Health Care 158 7.4.4 Benefits and Limitations 160 7.5 Discussion 160 7.6 Conclusion 164 References 164 8 Ontology-Based Case Retrieval in an E-Mental Health Intelligent Information System 167; Georgia Kaoura, Konstantinos Kovas and Basilis Boutsinas 8.1 Introduction 167 8.2 Literature Survey 170 8.3 Problem Identified 173 8.4 Proposed Solution 174 8.4.1 The PAVEFS Ontology 174 8.4.2 Knowledge Base 179 8.4.3 Reasoning 180 8.4.4 User Interaction 182 8.5 Pros and Cons of Solution 183 8.5.1 Evaluation Methodology and Results 183 8.5.2 Evaluation Methodology 185 8.5.2.1 Evaluation Tools 186 8.5.2.2 Resu
• Edition: 1st
• Publisher Details: Hoboken : Wiley-Scrivener
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 610.285; Information storage and retrieval systems -- Medical care; Medical informatics; Health services administration -- Data processing; Ontologies (Information retrieval); Querying (Computer science); Internet of things; Machine learning
• Languages: English
• ISBNs: 9781119641384
• Related ISBNs: 9781119641360
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
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