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Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics. Группа авторовЧитать онлайн книгу.

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics - Группа авторов


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      1  Cover

      2  Title Page

      3  Copyright

      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


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