Semantic Web for Effective Healthcare Systems
Herausgegeben:Jain, Vishal; Chatterjee, Jyotir Moy; Bansal, Ankita; Jain, Abha
Semantic Web for Effective Healthcare Systems
Herausgegeben:Jain, Vishal; Chatterjee, Jyotir Moy; Bansal, Ankita; Jain, Abha
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Ziel dieses Buchs ist eine Analyse, wie das Semantic Web nach aktuellem Stand eingesetzt wird, um das Problem der Integration und Interoperabilität von Gesundheitsdaten zu lösen, wobei es fortschrittliche Möglichkeiten zur Datenverknüpfung bietet, um die Suche nach und das Abrufen von medizinischen Daten zu verbessern. In einigen Kapiteln werden die Instrumente und Ansätze zur semantischen Analyse von Gesundheitsdaten und zur Wissenserschließung analysiert. Außerdem wird die Rolle der semantischen Technologien bei der Extraktion und Umwandlung von Gesundheitsdaten vor der Speicherung in…mehr
- Enabling Healthcare 4.0 for Pandemics217,99 €
- Advanced Healthcare Systems246,99 €
- Computational Intelligence and Healthcare Informatics250,99 €
- Cognitive Intelligence and Big Data in Healthcare234,99 €
- Innovative Engineering with AI Applications246,99 €
- Advanced Analytics and Deep Learning Models229,99 €
- Bioinformatics and Medical Applications250,99 €
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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
- Produktdetails
- Verlag: Wiley & Sons / Wiley-Scrivener
- Artikelnr. des Verlages: 1W119762290
- 1. Auflage
- Seitenzahl: 352
- Erscheinungstermin: 9. Dezember 2021
- Englisch
- Abmessung: 234mm x 160mm x 25mm
- Gewicht: 632g
- ISBN-13: 9781119762294
- ISBN-10: 1119762294
- Artikelnr.: 61111661
- Verlag: Wiley & Sons / Wiley-Scrivener
- Artikelnr. des Verlages: 1W119762290
- 1. Auflage
- Seitenzahl: 352
- Erscheinungstermin: 9. Dezember 2021
- Englisch
- Abmessung: 234mm x 160mm x 25mm
- Gewicht: 632g
- ISBN-13: 9781119762294
- ISBN-10: 1119762294
- Artikelnr.: 61111661
Acknowledgment xix
1 An Ontology-Based Contextual Data Modeling for Process Improvement in Healthcare 1
A. M. Abirami and A. Askarunisa
1.1 Introduction 1
1.1.1 Ontology-Based Information Extraction 3
1.1.2 Ontology-Based Knowledge Representation 4
1.2 Related Work 5
1.3 Motivation 8
1.4 Feature Extraction 9
1.4.1 Vector Space Model 10
1.4.2 Latent Semantic Indexing (LSI) 11
1.4.3 Clustering Techniques 12
1.4.4 Topic Modeling 12
1.5 Ontology Development 17
1.5.1 Ontology-Based Semantic Indexing (OnSI) Model 17
1.5.2 Ontology Development 18
1.5.3 OnSI Model Evaluation 19
1.5.4 Metrics Analysis 23
1.6 Dataset Description 24
1.7 Results and Discussions 25
1.7.1 Discussion 1 29
1.7.2 Discussion 2 29
1.7.3 Discussion 3 30
1.8 Applications 31
1.9 Conclusion 32
1.10 Future Work 33
References 33
2 Semantic Web for Effective Healthcare Systems: Impact and Challenges 39
Hemendra Shankar Sharma and Ashish Sharma
2.1 Introduction 40
2.2 Overview of the Website in Healthcare 45
2.2.1 What is Website? 45
2.2.2 Types of Website 45
2.2.2.1 Static Website 45
2.2.2.2 Dynamic Website 46
2.2.3 What is Semantic Web? 46
2.2.4 Role of Semantic Web 47
2.2.4.1 Pros and Cons of Semantic Web 49
2.2.4.2 Impact on Patient 51
2.2.4.3 Impact on Practitioner 52
2.2.4.4 Impact on Researchers 52
2.3 Data and Database 53
2.3.1 What is Data? 54
2.3.2 What is Database? 54
2.3.3 Source of Data in the Healthcare System 54
2.3.3.1 Electronic Health Record (EHR) 55
2.3.3.2 Biomedical Image Analysis 56
2.3.3.3 Sensor Data Analysis 57
2.3.3.4 Genomic Data Analysis 57
2.3.3.5 Clinical Text Mining 58
2.3.3.6 Social Media 59
2.3.4 Why Are Databases Important? 60
2.3.5 Challenges With the Database in the Healthcare System 61
2.4 Big Data and Database Security and Protection 61
2.4.1 What is Big Data 61
2.4.2 Five V's of Big Data 62
2.4.2.1 Volume 62
2.4.2.2 Variety 63
2.4.2.3 Velocity 63
2.4.2.4 Veracity 64
2.4.2.5 Value 65
2.4.3 Architectural Framework of Big Data 65
2.4.4 Data Protection Versus Data Security in Healthcare 67
2.4.4.1 Phishing Attacks 67
2.4.4.2 Malware and Ransomware 67
2.4.4.3 Cloud Threats 67
2.4.5 Technology in Use to Secure the Healthcare Data 68
2.4.5.1 Access Control Policy 69
2.4.6 Monitoring and Auditing 69
2.4.7 Standard for Data Protection 70
2.4.7.1 Healthcare Standard in India 70
2.4.7.2 Security Technical Standards 71
2.4.7.3 Administrative Safeguards Standards 71
2.4.7.4 Physical Safeguard Standards 71
References 71
3 Ontology-Based System for Patient Monitoring 75
R. Mervin, Tintu Thomas and A. Jaya
3.1 Introduction 76
3.1.1 Basics of Ontology 77
3.1.2 Need of Ontology in Patient Monitoring 78
3.2 Literature Review 78
3.2.1 Uses of Ontology in Various Domains 78
3.2.2 Ontology in Patient Monitoring System 80
3.3 Architectural Design 80
3.3.1 Phases of Patient Monitoring System 82
3.3.2 Reasoner in Patient Monitoring 87
3.4 Experimental Results 88
Acknowledgment xix
1 An Ontology-Based Contextual Data Modeling for Process Improvement in Healthcare 1
A. M. Abirami and A. Askarunisa
1.1 Introduction 1
1.1.1 Ontology-Based Information Extraction 3
1.1.2 Ontology-Based Knowledge Representation 4
1.2 Related Work 5
1.3 Motivation 8
1.4 Feature Extraction 9
1.4.1 Vector Space Model 10
1.4.2 Latent Semantic Indexing (LSI) 11
1.4.3 Clustering Techniques 12
1.4.4 Topic Modeling 12
1.5 Ontology Development 17
1.5.1 Ontology-Based Semantic Indexing (OnSI) Model 17
1.5.2 Ontology Development 18
1.5.3 OnSI Model Evaluation 19
1.5.4 Metrics Analysis 23
1.6 Dataset Description 24
1.7 Results and Discussions 25
1.7.1 Discussion 1 29
1.7.2 Discussion 2 29
1.7.3 Discussion 3 30
1.8 Applications 31
1.9 Conclusion 32
1.10 Future Work 33
References 33
2 Semantic Web for Effective Healthcare Systems: Impact and Challenges 39
Hemendra Shankar Sharma and Ashish Sharma
2.1 Introduction 40
2.2 Overview of the Website in Healthcare 45
2.2.1 What is Website? 45
2.2.2 Types of Website 45
2.2.2.1 Static Website 45
2.2.2.2 Dynamic Website 46
2.2.3 What is Semantic Web? 46
2.2.4 Role of Semantic Web 47
2.2.4.1 Pros and Cons of Semantic Web 49
2.2.4.2 Impact on Patient 51
2.2.4.3 Impact on Practitioner 52
2.2.4.4 Impact on Researchers 52
2.3 Data and Database 53
2.3.1 What is Data? 54
2.3.2 What is Database? 54
2.3.3 Source of Data in the Healthcare System 54
2.3.3.1 Electronic Health Record (EHR) 55
2.3.3.2 Biomedical Image Analysis 56
2.3.3.3 Sensor Data Analysis 57
2.3.3.4 Genomic Data Analysis 57
2.3.3.5 Clinical Text Mining 58
2.3.3.6 Social Media 59
2.3.4 Why Are Databases Important? 60
2.3.5 Challenges With the Database in the Healthcare System 61
2.4 Big Data and Database Security and Protection 61
2.4.1 What is Big Data 61
2.4.2 Five V's of Big Data 62
2.4.2.1 Volume 62
2.4.2.2 Variety 63
2.4.2.3 Velocity 63
2.4.2.4 Veracity 64
2.4.2.5 Value 65
2.4.3 Architectural Framework of Big Data 65
2.4.4 Data Protection Versus Data Security in Healthcare 67
2.4.4.1 Phishing Attacks 67
2.4.4.2 Malware and Ransomware 67
2.4.4.3 Cloud Threats 67
2.4.5 Technology in Use to Secure the Healthcare Data 68
2.4.5.1 Access Control Policy 69
2.4.6 Monitoring and Auditing 69
2.4.7 Standard for Data Protection 70
2.4.7.1 Healthcare Standard in India 70
2.4.7.2 Security Technical Standards 71
2.4.7.3 Administrative Safeguards Standards 71
2.4.7.4 Physical Safeguard Standards 71
References 71
3 Ontology-Based System for Patient Monitoring 75
R. Mervin, Tintu Thomas and A. Jaya
3.1 Introduction 76
3.1.1 Basics of Ontology 77
3.1.2 Need of Ontology in Patient Monitoring 78
3.2 Literature Review 78
3.2.1 Uses of Ontology in Various Domains 78
3.2.2 Ontology in Patient Monitoring System 80
3.3 Architectural Design 80
3.3.1 Phases of Patient Monitoring System 82
3.3.2 Reasoner in Patient Monitoring 87
3.4 Experimental Results 88