Читать книгу Biomedical Data Mining for Information Retrieval - Группа авторов - Страница 2
Table of Contents
Оглавление1 Cover
4 Preface Introduction Organization of the Book Concluding Remarks
5 1 Mortality Prediction of ICU Patients Using Machine Learning Techniques 1.1 Introduction 1.2 Review of Literature 1.3 Materials and Methods 1.4 Result and Discussion 1.5 Conclusion 1.6 Future Work References
6 2 Artificial Intelligence in Bioinformatics 2.1 Introduction 2.2 Recent Trends in the Field of AI in Bioinformatics 2.3 Data Management and Information Extraction 2.4 Gene Expression Analysis 2.5 Role of Computation in Protein Structure Prediction 2.6 Application in Protein Folding Prediction 2.7 Role of Artificial Intelligence in Computer-Aided Drug Design 2.8 Conclusions References
7 3 Predictive Analysis in Healthcare Using Feature Selection 3.1 Introduction 3.2 Literature Review 3.3 Dataset Description 3.4 Feature Selection 3.5 Feature Selection Methods 3.6 Methodology 3.7 Experimental Results and Analysis 3.8 Conclusion References
8 4 Healthcare 4.0: An Insight of Architecture, Security Requirements, Pillars and Applications 4.1 Introduction 4.2 Basic Architecture and Components of e-Health Architecture 4.3 Security Requirements in Healthcare 4.0 4.4 ICT Pillar’s Associated With HC4.0 4.5 Healthcare 4.0’s Applications-Scenarios 4.6 Conclusion References
9 5 Improved Social Media Data Mining for Analyzing Medical Trends 5.1 Introduction 5.2 Literature Survey 5.3 Basic Data Mining Clustering Technique 5.4 Research Methodology 5.5 Results and Discussion 5.6 Conclusion & Future Scope References
10 6 Bioinformatics: An Important Tool in Oncology 6.1 Introduction 6.2 Cancer—A Brief Introduction 6.3 Bioinformatics—A Brief Introduction 6.4 Bioinformatics—A Boon for Cancer Research 6.5 Applications of Bioinformatics Approaches in Cancer 6.6 Bioinformatics: A New Hope for Cancer Therapeutics 6.7 Conclusion References
11 7 Biomedical Big Data Analytics Using IoT in Health Informatics 7.1 Introduction 7.2 Biomedical Big Data 7.3 Healthcare Internet of Things (IoT) 7.4 Studies Related to Big Data Analytics in Healthcare IoT 7.5 Challenges for Medical IoT & Big Data in Healthcare 7.6 Conclusion References
12 8 Statistical Image Analysis of Drying Bovine Serum Albumin Droplets in Phosphate Buffered Saline 8.1 Introduction 8.2 Experimental Methods 8.3 Results 8.4 Discussions 8.5 Conclusions Acknowledgments References
13 9 Introduction to Deep Learning in Health Informatics 9.1 Introduction 9.2 Deep Learning in Health Informatics 9.3 Medical Informatics 9.4 Bioinformatics 9.5 Pervasive Sensing 9.6 Public Health 9.7 Deep Learning Limitations and Challenges in Health Informatics References
14 10 Data Mining Techniques and Algorithms in Psychiatric Health: A Systematic Review 10.1 Introduction 10.2 Techniques and Algorithms Applied 10.3 Analysis of Major Health Disorders Through Different Techniques 10.4 Conclusion References
15 11 Deep Learning Applications in Medical Image Analysis 11.1 Introduction 11.2 Deep Learning Models and its Classification 11.3 Convolutional Neural Networks (CNN)—A Popular Supervised Deep Model 11.4 Deep Learning Advancements—A Biological Overview 11.5 Conclusion and Discussion References
16 12 Role of Medical Image Analysis in Oncology 12.1 Introduction 12.2 Cancer 12.3 Medical Imaging 12.4 Diagnostic Approaches for Cancer 12.5 Conclusion References
17 13 A Comparative Analysis of Classifiers Using Particle Swarm Optimization-Based Feature Selection 13.1 Introduction 13.2 Feature Selection for Classification 13.3 Use of WEKA Tool 13.4 Conclusion and Future Work References
18 Index
