Читать книгу Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics - Группа авторов - Страница 2
Table of Contents
Оглавление1 Cover
4 Preface
5 1 An Introduction to Big Data Analytics Techniques in Healthcare 1.1 Introduction 1.2 Big Data in Healthcare 1.3 Areas of Big Data Analytics in Medicine 1.4 Healthcare as a Big Data Repository 1.5 Applications of Healthcare Big Data 1.6 Challenges in Big Data Analytics 1.7 Big Data Privacy and Security 1.8 Conclusion 1.9 Future Work References
6 2 Identify Determinants of Infant and Child Mortality Based Using Machine Learning: Case Study on Ethiopia 2.1 Introduction 2.2 Literature Review 2.3 Methodology and Data Source 2.4 Implementation and Results 2.5 Conclusion References
7 3 Pre-Trained CNN Models in Early Alzheimer’s Prediction Using Post-Processed MRI 3.1 Introduction 3.2 Experimental Study 3.3 Data Exploration 3.4 OASIS Dataset Pre-Processing 3.5 Alzheimer’s 4-Class-MRI Features Extraction 3.6 Alzheimer 4-Class MRI Image Dataset 3.7 RMSProp (Root Mean Square Propagation) 3.8 Activation Function 3.9 Batch Normalization 3.10 Dropout 3.11 Result—I 3.12 Conclusion and Future Work Acknowledgement References
8 4 Robust Segmentation Algorithms for Retinal Blood Vessels, Optic Disc, and Optic Cup of Retinal Images in Medical Imaging 4.1 Introduction 4.2 Basics of Proposed Methods 4.3 Experimental Results and Discussion 4.4 Conclusion References
9 5 Analysis of Healthcare Systems Using Computational Approaches 5.1 Introduction 5.2 AI & ML Analysis in Health Systems 5.3 Healthcare Intellectual Approaches 5.4 Precision Approaches to Medicine 5.5 Methodology of AI, ML With Healthcare Examples 5.6 Big Analytic Data Tools 5.7 Discussion 5.8 Conclusion References
10 6 Expert Systems in Behavioral and Mental Healthcare: Applications of AI in Decision-Making and Consultancy 6.1 Introduction 6.2 AI Methods 6.3 Turing Test 6.4 Barriers to Technologies 6.5 Advantages of AI for Behavioral & Mental Healthcare 6.6 Enhanced Self-Care & Access to Care 6.7 Other Considerations 6.8 Expert Systems in Mental & Behavioral Healthcare 6.9 Dynamical Approaches to Clinical AI and Expert Systems 6.10 Conclusion 6.11 Future Prospects References
11 7 A Mathematical-Based Epidemic Model to Prevent and Control Outbreak of Corona Virus 2019 (COVID-19) 7.1 Introduction 7.2 Related Work 7.3 Proposed Frameworks 7.4 Results and Discussion 7.5 Conclusion References
12 8 An Access Authorization Mechanism for Electronic Health Records of Blockchain to Sheathe Fragile Information 8.1 Introduction 8.2 Related Work 8.3 Need for Blockchain in Healthcare 8.4 Proposed Frameworks 8.5 Use Cases 8.6 Discussions 8.7 Challenges and Limitations 8.8 Future Work 8.9 Conclusion References
13 9 An Epidemic Graph’s Modeling Application to the COVID-19 Outbreak 9.1 Introduction 9.2 Related Work 9.3 Theoretical Approaches 9.4 Frameworks 9.5 Evaluation of COVID-19 Outbreak 9.6 Conclusions and Future Works References
14 10 Big Data and Data Mining in e-Health: Legal Issues and Challenges 10.1 Introduction 10.2 Big Data and Data Mining in e-Health 10.3 Big Data and e-Health in India 10.4 Legal Issues Arising Out of Big Data and Data Mining in e-Health 10.5 Big Data and Issues of Privacy in e-Health 10.6 Conclusion and Suggestions References
15 11 Basic Scientific and Clinical Applications 11.1 Introduction 11.2 Case Study-1: Continual Learning Using ML for Clinical Applications 11.3 Case Study-2 11.4 Case Study-3: ML Will Improve the RadiologyPatient Experience 11.5 Case Study-4: Medical Imaging AI with Transition from Academic Research to Commercialization 11.6 Case Study-5: ML will Benefit All Medical Imaging ‘ologies’ 11.7 Case Study-6: Health Providers will Leverage Data Hubs to Unlock the Value of Their Data 11.8 Conclusion References
16 12 Healthcare Branding Through Service Quality 12.1 Introduction to Healthcare 12.2 Quality in Healthcare 12.3 Service Quality 12.4 Conclusion and Road Ahead References
17 Index
