Bioinformatics and Medical Applications

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BIOINFORMATICS AND MEDICAL APPLICATIONS
The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology.
Audience Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms

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9 Chapter 9Figure 9.1 Estimated healthcare IoT device installation [14].Figure 9.2 System design flow chart.Figure 9.3 CNN architecture.Figure 9.4 Block diagram.Figure 9.5 Various classes of tumors.Figure 9.6 Codes used to train our CNN model.Figure 9.7 Loading page.Figure 9.8 Result displayed.Figure 9.9 Result displayed.Figure 9.10 About section.Figure 9.11 Accuracy score.Figure 9.12 Comparison chart.

10 Chapter 10Figure 10.1 Standard level of criteria air pollutants and their sources with hea...Figure 10.2 World regional capital city ranking, 2018 (Website: IQAir).Figure 10.3 Diagrammatic representation of component of Hawan Samagri along with...Figure 10.4 Society residents chanting Vedic Mantras and performing community Ya...Figure 10.5 People in Indian and South Asian continent celebrating Holi Festival...Figure 10.6 CCD image sensor for capturing images (Website: Wikipedia).Figure 10.7 IR proximity sensor for distance measurement (Website: Flipkart.com)...Figure 10.8 In Yajna, besides burning material objects, chanting and praying are...Figure 10.9 The IoT-based sensors capturing the humidity and temperature data fr...Figure 10.10 Measurement of different parameters of AQI on November 16, 2019 (Ya...Figure 10.11 Measurement of different parameters of AQI on November 17, 2019 (Ya...Figure 10.12 Measurement of different parameters of AQI on November 18, 2019 (Ya...Figure 10.13 Measurement of different parameters of AQI on November 19, 2019 (Ya...Figure 10.14 Comparative analysis of emission of different gaseous elements and ...Figure 10.15 Comparative analysis of averaged environmental parameters in fume e...Figure 10.16 Study of the comparative analysis of stability of the environment b...Figure 10.17 Collective recital of mantra helps in depression treatment and slee...

11 Chapter 11Figure 11.1 Analysis w.r.t. attribute-transformation clusters.Figure 11.2 Analysis w.r.t. rate-transformation clusters.

12 Chapter 12Figure 12.1 Benefits of Yagya or Yagyopathy [56].Figure 12.2 Graphical analysis for fasting blood sugar with the respect to the a...Figure 12.3 Graphical presentation for FBST PRANDAL blood sugar with the respect...Figure 12.4 Graphical representation to compare the sugar level results in 4-mon...Figure 12.5 Graphical representation to compare the FVC and FEV1 on parameters.Figure 12.6 Graphical representation to compare subject’s data on different date...Figure 12.7 Radiation variation of different electronic gadgets of subjects (lap...Figure 12.8 Left-hand analysis of happiness index of different subjects.Figure 12.9 Right-hand analysis of happiness index of different subjects.Figure 12.10 Age vs. happiness index (right hand).Figure 12.11 Age vs. happiness index (left hand).

13 Chapter 13Figure 13.1 Taxonomy.Figure 13.2 Three-layer architecture for remote health monitoring.

14 Chapter 14Figure 14.1 The Myo armbands usage for Sign Language Recognition.Figure 14.2 Smart ring + watch setup to detect movements of the finger during th...Figure 14.3 Figure shows the start, middle, and end frames along with the motion...Figure 14.4 Images showing annotations of various images extracted from ASLLVD a...Figure 14.5 Image showing variation in the training and test set images. The var...Figure 14.6 Image showing the capturing system used in the SMILE Swiss German Si...Figure 14.7 Image showing the contents of SMILE Swiss German Sign Language Datas...Figure 14.8 Figure representing the recording procedure for the SIGNUM corpus [1...Figure 14.9 The figure represents the 32 alphabets and the number of images obta...Figure 14.10 This table summarizes some glove sensor systems among which systems...Figure 14.11 Image showing the 3D reconstruction through Kinect-based images. Im...Figure 14.12 Figure representing usage of multi-feature extraction from an image...Figure 14.13 Capsule network for the Sign Language Recognition task [29].Figure 14.14 Real-Time Sign Language Recognition system using Pose Estimation an...Figure 14.15 Network showing the feature extraction and the usage of LSTM to per...Figure 14.16 Difference between a Sign Language Recognition and a Sign Language ...Figure 14.17 Image showing the Neural Sign Language Translation by employing seq...Figure 14.18 Image showing the different human body parts take into account and ...

List of Tables

1 Chapter 1 Table 1.1 Comparative analysis of prediction techniques. Table 1.2 Dataset attributes.

2 Chapter 4Table 4.1 Confusion matrix for binary classification.Table 4.2 Performance analysis of different classifiers.

3 Chapter 5Table 5.1 List of major biological network data resources.

4 Chapter 6Table 6.1 Details of the extracted features.Table 6.2 Accuracy score of classification models.

5 Chapter 8Table 8.1 The table contains a list of datasets in 2D and 3D human pose estimati...

6 Chapter 11Table 11.1 Parameters used in simulation.

7 Chapter 12Table 12.1 Yagya decreases air pollution [60].Table 12.2 Comparison of results.Table 12.3 Yagyopathy experiment on diabetic patient.Table 12.4 Final result.

Guide

1 Cover

2 Table of Contents

3 Title Page

4 Copyright

5 Preface

6 Begin Reading

7 Index

8 End User License Agreement

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