Handbook on Intelligent Healthcare Analytics

1 Cover

2 Title Page

3 Copyright

4 Preface

5 1 An Introduction to Knowledge Engineering and Data Analytics 1.1 Introduction 1.2 Knowledge and Knowledge Engineering 1.3 Knowledge Engineering as a Modelling Process 1.4 Tools 1.5 What are KBSs? 1.6 Guided Random Search and Network Techniques 1.7 Genetic Algorithms 1.8 Artificial Neural Networks 1.9 Conclusion References

6 2 A Framework for Big Data Knowledge Engineering 2.1 Introduction 2.2 Big Data in Knowledge Engineering 2.3 Proposed System 2.4 Results and Discussion 2.5 Conclusion References

7 3 Big Data Knowledge System in Healthcare 3.1 Introduction 3.2 Overview of Big Data 3.3 Big Data Tools and Techniques 3.4 Big Data Knowledge System in Healthcare 3.5 Big Data Applications in the Healthcare Sector 3.6 Challenges with Healthcare Big Data 3.7 Conclusion References

8 4 Big Data for Personalized Healthcare 4.1 Introduction 4.2 Related Literature 4.3 System Analysis and Design 4.4 System Implementation 4.5 Results and Discussion 4.6 Conclusion References

9 5 Knowledge Engineering for AI in Healthcare 5.1 Introduction 5.2 Overview 5.3 Applications of Knowledge Engineering in AI for Healthcare 5.4 Conclusion References

10 6 Business Intelligence and Analytics from Big Data to Healthcare 6.1 Introduction 6.2 Related Works 6.3 Conceptual Healthcare Stock Prediction System 6.4 Implementation and Result Discussion 6.5 Comparisons of Healthcare Stock Prediction Framework 6.6 Conclusion and Future Enhancement References Books Web Citation

11 7 Internet of Things and Big Data Analytics for Smart Healthcare 7.1 Introduction 7.2 Literature Survey 7.3 Smart Healthcare Using Internet of Things and Big Data Analytics 7.4 Security for Internet of Things 7.5 Conclusion References

12 8 Knowledge-Driven and Intelligent Computing in Healthcare 8.1 Introduction 8.2 Literature Review 8.3 Framework for Health Recommendation System 8.4 Experimental Results 8.5 Conclusion and Future Perspective References

13 9 Secure Healthcare Systems Based on Big Data Analytics 9.1 Introduction 9.2 Healthcare Data 9.3 Recent Works in Big Data Analytics in Healthcare Data 9.4 Healthcare Big Data 9.5 Privacy of Healthcare Big Data 9.6 Privacy Right by Country and Organization 9.7 How Blockchain is Big Data Usable for Healthcare 9.8 Blockchain Threats and Medical Strategies Big Data Technology 9.9 Conclusion and Future Research References

14 10 Predictive and Descriptive Analysis for Healthcare Data 10.1 Introduction 10.2 Motivation 10.3 Conclusion References

15 11 Machine and Deep Learning Algorithms for Healthcare Applications 11.1 Introduction 11.2 Artificial Intelligence, Machine Learning, and Deep Learning 11.3 Machine Learning 11.4 Advantages of Using Deep Learning on Top of Machine Learning 11.5 Deep Learning Architecture 11.6 Medical Image Analysis using Deep Learning 11.7 Deep Learning in Chest X-Ray Images 11.8 Machine Learning and Deep Learning in Content-Based Medical Image Retrieval 11.9 Image Retrieval Performance Metrics 11.10 Conclusion References

16 12 Artificial Intelligence in Healthcare Data Science with Knowledge Engineering 12.1 Introduction 12.2 Literature Review 12.3 AI in Healthcare 12.4 Data Science and Knowledge Engineering for COVID-19 12.5 Proposed Architecture and Its Implementation 12.6 Conclusions and Future Work References

17 13 Knowledge Engineering Challenges in Smart Healthcare Data Analysis System 13.1 Introduction 13.2 Ongoing Research on Intelligent Decision Support System 13.3 Methodology and Architecture of the Intelligent Rule-Based System 13.4 Creating a Rule-Based System using Prolog 13.5 Results and Discussions 13.6 Conclusion 13.7 Acknowledgments References

18 14 Big Data in Healthcare: Management, Analysis, and Future Prospects 14.1 Introduction 14.2 Breast Cancer: Overview 14.3 State-of-the-Art Technology in Treatment of Cancer 14.4 Early Diagnosis of Breast Cancer: Overview 14.5 Literature Review 14.6 Machine Learning Algorithms 14.7 Result and Discussion 14.8 Experimental Result and Discussion 14.9 Conclusion References

19 15 Machine Learning for Information Extraction, Data Analysis and Predictions in the Healthcare System 15.1 Introduction 15.2 Machine Learning in Healthcare 15.3 Types of Learnings in Machine Learning 15.4 Types of Machine Learning Algorithms 15.5 Machine Learning for Information Extraction 15.6 Predictive Analysis in Healthcare 15.7 Conclusion References

20 16 Knowledge Fusion Patterns in Healthcare 16.1 Introduction 16.2 Related Work 16.3 Materials and Methods 16.4 Proposed System 16.5 Results and Discussion 16.6 Conclusion and Future Work References

21 17 Commercial Platforms for Healthcare Analytics: Health Issues for Patients with Sickle Cells 17.1 Introduction 17.2 Materials and Methods 17.3 Results and Discussion 17.4 Conclusion References

22 18 New Trends and Applications of Big Data Analytics for Medical Science and Healthcare 18.1 Introduction 18.2 Related Work 18.3 Convolutional Layer 18.4 Pooling Layer 18.5 Fully Connected Layer 18.6 Recurrent Neural Network 18.7 LSTM and GRU 18.8 Materials and Methods 18.9 Results and Discussions 18.10 Conclusion 18.11 Acknowledgement References

23 Index

24 End User License Agreement

1 Chapter 1 Figure 1.1Knowledge engineering. Figure 1.2Knowledge as modelling process. Figure 1.3KBE.

2 Chapter 2 Figure 2.1Traditional Bayesian Neural Network disaster prediction from the data... Figure 2.2Proposed system for predicting disaster using improved Bayesian hidde... Figure 2.3Total number of disaster analysis using improved Bayesian Markov chai... Figure 2.4Changes from various impacts from natural disaster. Figure 2.5Economic damage changes a prediction analysis. Figure 2.6Boxplot view of natural disaster on various entity.

3 Chapter 3 Figure 3.1Dimensions of big data. Figure 3.2Big data value creation flow. Figure 3.3Different sources of healthcare data. Figure 3.4Knowledge discovery process of big data in healthcare.

4 Chapter 4 Figure 4.1Architecture diagram. Figure 4.2Functional block diagram. Figure 4.3Storage block. Figure 4.4Reporting block. Figure 4.5Analysis block. Figure 4.6Management block. Figure 4.7Use case diagram. Figure 4.8Sequence diagram. Figure 4.9Class diagram. Figure 4.10Cases of patients. Figure 4.11Notifications of medicines to endpoints. Figure 4.12Admin dashboard.

5 Chapter 5 Figure 5.1Process of knowledge engineering. Figure 5.2Data science and knowledge engineering.

6 Chapter 6 Figure 6.1Conceptual healthcare stock prediction system. Figure 6.2Overview of business intelligence and analytics framework. Figure 6.3Illustration of healthcare stock prediction system. Figure 6.4Prediction of the closing price using LR. Figure 6.5Prediction of the closing price using ARIMA. Figure 6.6Prediction of the closing price using LSTM. Figure 6.7Prediction of the closing price using LR. Figure 6.8Prediction of the closing price using ARIMA. Figure 6.9Prediction of the closing price using LSTM. Figure 6.10Prediction of the closing price using LR. Figure 6.11Prediction of the closing price using ARIMA.