Biomedical Data Mining for Information Retrieval. Группа авторов

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

      19  End User License Agreement

      Guide

      1  Cover

      2  Table of Contents

      3  Title page

      4  Copyright

      5  Preface

      6  Begin Reading

      7  Index

      8  End User License Agreement

      List of Illustrations

      1 Chapter 1Figure 1.1 Step by step process for mortality prediction.Figure 1.2 The FLANN based mortality prediction model.Figure 1.3 Convergence characteristics of FA-FLANN based mortality prediction mo...

      2 Chapter 2Figure 2.1 The different level of organization of protein.

      3 Chapter 3Figure 3.1 Diabetes dataset class distribution.Figure 3.2 Class distribution of hepatitis dataset.Figure 3.3 Flow chart of the tasks carried out in this chapter.

      4 Chapter 4Figure 4.1 Basic architecture and components of e-health architecture.Figure 4.2 Healthcare 4.0 protection and security necessities.

      5 Chapter 5Figure 5.1 Steps involved in Data mining process. http://www.lastnightstudy.com/...Figure 5.2 Components of data mining system. https://www.ques10.com/p/9209/expla...Figure 5.3 Major Social media sites. https://www.securitymagazine.com/articles/8...Figure 5.4 Social network representation using graph. https://www.javatpoint.com...Figure 5.5 An example of clustering. https://www.analyticsvidhya.com/blog/2013/1...Figure 5.6 Partition clustering [18].Figure 5.7 Hierarchical clustering [19].Figure 5.8 Obstacle in Constraint-Based Clustering [42].Figure 5.9 Decision tree [42].Figure 5.10 Categorization of social media data [43].Figure 5.11 Frame work for proposed system.Figure 5.12 Basic steps of page rank algorithm. https://www.analyticsvidhya.com/...Figure 5.13 Output generated after Pre processing step. Stop Word algorithm has ...Figure 5.14 (a) Pre processing; (b) Graph clustering.Figure 5.15 Apply k-mean algorithm.Figure 5.16 Generation of clustering data.Figure 5.17 Output of K-means algorithm.Figure 5.18 Apply back propagation algorithm.Figure 5.19 Result of clustering.Figure 5.20 Classified data.Figure 5.21 Performance comparison of proposed algorithm and other existing meth...Figure 5.22 Execution time.

      6 Chapter 6Figure 6.1 Bioinformatics tools used in cancer research.Figure