Next Generation Healthcare Systems Using Soft Computing Techniques 1st Edition by Rekh Ram Janghel, Rohit Raja, Korhan Cengiz, Hiral Raja ISBN 9781032107974 1032107979

Next Generation Healthcare Systems Using Soft Computing Techniques 1st Edition by Rekh Ram Janghel, Rohit Raja, Korhan Cengiz, Hiral Raja – Ebook PDF Instant Download/Delivery: 9781032107974 ,1032107979
Full download Next Generation Healthcare Systems Using Soft Computing Techniques 1st Edition after payment

Product details:

ISBN 10: 1032107979
ISBN 13: 9781032107974
Author: Rekh Ram Janghel, Rohit Raja, Korhan Cengiz, Hiral Raja

Next Generation Healthcare Systems Using Soft Computing Techniques 1st Edition Table of contents:

Chapter 1 Computational Intelligence for Healthcare

1.1 Introduction

1.1.1 Artificial Neural Network

1.1.2 Restricted Boltzman Machines

1.1.3 Support Vector Machines

1.1.4 Evolutionary Algorithms

1.1.5 Fuzzy Systems

1.1.6 Swarm Intelligence

1.2 Issues and Challenges

1.2.1 Data Inconsistency, Inaccuracy, and Missing Values

1.2.2 Imbalanced Data

1.2.3 Data Collection Cost

1.2.4 Huge Data Volume

1.2.5 Ethical and Privacy Issues

1.3 Feature Engineering

1.3.1 Feature Extraction

1.3.2 Feature Selection

1.3.3 Feature Weighting

1.3.4 Introduction to Gene Expression Dataset

1.3.5 Challenges in Gene Expression Data

1.3.6 Feature Selection and Classification of Gene Expression Data Using Binary Jaya Algorithm

1.4 Available Resources

1.5 Conclusion

References

Chapter 2 Analysis of Recurrent Neural Network and Convolution Neural Network Techniques in Blood Cell Classification

2.1 Introduction

2.1.1 Deep Learning Techniques

2.1.2 Medical Imaging/White Blood Cell Classification

2.2 Dataset

2.3 Analysis of Deep Learning Techniques

2.3.1 Recurrent Neural Network

2.3.2 Convolution Neural Network

2.3.3 Convolution Neural Network Experiment Design and Results

2.4 Conclusions

References

Chapter 3 Evaluating the Effectiveness of the Convolution Neural Network in Detecting Brain Tumors

3.1 Introduction

3.1.1 Deep Learning and Convolution Neural Network

3.1.2 Medical Imagery/Brain Tumor Detection

3.2 Related Work

3.3 Dataset

3.4 Evaluation of Convolution Neural Network Architectures

3.4.1 Test Case # 1

3.4.2 Test Case # 2

3.4.3 Test Case # 3

3.5 Conclusions

References

Chapter 4 Implementation of Machine Learning in Color Perception and Psychology: A Review

4.1 Introduction

4.1.1 Motivation

4.1.2 Related Works

4.1.3 Contribution

4.2 Application Areas

4.2.1 Food and Breed Hunting for Animals

4.2.2 Application in Color Constancy

4.2.3 Color Blindness Detection

4.2.4 Sentiment Analysis Based on Color Attributes

4.2.5 Application in Agriculture Using Color Classification

4.3 Deep Learning Methods Used in Color Psychology Analysis

4.3.1 Conditional GAN

4.3.2 Convolution Neural Network

4.3.3 Bidirectional Long Short Term Memory

4.3.4 Probabilistic Neural Network

4.3.5 VGG-16

4.3.6 DenseNet

4.4 Conclusion

References

Chapter 5 Early Recognition of Dynamic Sleeping Patterns Associated with Rapid Eyeball Movement Sleep Behavior Disorder of Apnea Patients Using Neural Network Techniques

5.1 Introduction

5.2 Methodologies

5.3 Data Collection

5.4 Preprocessing of Data and Feature Extraction Using Wavelet Packet Decomposition (WPD)

5.5 Feature Classification by Deep Neural Network (DNN) Classifier

5.6 Long Short Term Memory (LSTM) Technique

5.7 Results and Discussions

5.8 Conclusion

References

Chapter 6 Smart Attendance cum Health Check-up Machine for Students/Villagers/Company Employees

6.1 Introduction

6.2 Overview of Various Possible Smart Attendance Systems

6.2.1 Proposed Solution

6.2.2 Face Recognition System

6.3 Health Parameters and Stress Detection

6.3.1 Eye Blink Detection

6.3.2 Emotion Detection

6.4 Physiological Parameters and Sensors Description

6.4.1 Body Temperature

6.4.2 Blood SpO2 Level

6.4.3 Heart Rate

6.5 Hardware and Sensors Used

6.5.1 MLX 90614 Temperature Sensor

6.5.2 MAX 30100 Heart Rate and Blood SpO2 Sensor

6.5.3 Arduino UNO

6.6 Software Tools

6.6.1 Arduino IDE

6.6.2 Tkinter

6.7 Outcomes and Result

6.7.1 Face Recognition

6.7.2 Emotion Recognition and Eye-Blink Rate Detection

6.7.3 Data from Sensors

6.8 Conclusion

Acknowledgement

References

Chapter 7 Oral Histopathological Photomicrograph Classification Using Deep Learning

7.1 Introduction

7.2 Related Work

7.3 Present Diagnosing Method for Oral Cancer

7.4 Materials and Methods

7.4.1 Deep-Learning Combined with SVM Approach

7.4.2 Transfer Learning of the Deep-Learning Model’s Approach

7.4.3 Fusion of the Results Obtained from Transfer Learning and SVM Process

7.5 Results and Discussions

7.5.1 Comparison of the Results with Other Related Works

7.6 Conclusion

References

Chapter 8 Prediction of Stage of Alzheimer’s Disease DenseNet Deep Learning Model

8.1 Introduction

8.2 Literature Survey

8.3 Methodology

8.3.1 Deep Learning Techniques

8.3.2 Dataset

8.3.3 Data Preprocessing

8.3.4 Network Architecture

8.3.5 DenseNet

8.4 Experiment and Result Discussion

8.4.1 Using Machine Learning

8.4.2 Using Deep Learning

8.5 Conclusion

References

Chapter 9 An Insight of Deep Learning Applications in the Healthcare Industry

9.1 Introduction

9.2 Drug Discovery

9.3 Medical Image and Diagnostics

9.4 Clinical Trials

9.5 Patient Monitoring and Personalized Treatment

9.6 Chatbot Using NLP

9.7 Health Insurance and Fraud Detection

9.8 Medical Diagnosis

9.9 Future Development

References

Chapter 10 Expand Patient Care with AWS Cloud for Remote Medical Monitoring

10.1 Introduction

10.2 Literature Review

10.3 Cloud Healthcare Management

10.3.1 Cloud Computing Models

10.3.2 Deployment Models

10.3.3 Advantages of Cloud Computation

10.4 Amazon Web Services

10.4.1 Compute

10.4.2 Storage

10.4.3 Amazon Machine Learning

10.4.4 Big Data Analysis in AWS

10.5 Cloud Pricing Strategy

10.6 AWS – Healthcare Solutions

10.7 Conclusion

References

Chapter 11 Privacy and Security Solution in Wireless Sensor Network for IoT in Healthcare System

11.1 Introduction

11.2 Classification of WSNs Protocols

11.2.1 Data-Centric Routing Protocol

11.2.2 Multiple Path Routing Protocol

11.2.3 Hierarchical Routing Protocol

11.2.4 Routing Protocol Based on Location

11.2.5 Mobility-Based Routing Protocol

11.2.6 Quality of Service-Based Routing Protocol

11.3 Privacy and Security Issues in WSN

11.3.1 Security and Privacy Issues

11.3.2 Clone Attack

11.3.3 Selective Forwarding Attack

11.4 Security and Privacy Solutions

11.4.1 Use of Effective Key Management

11.4.2 Use of Efficient Public Key Infrastructure

11.4.3 Effective Use of Multiclass Nodes

11.4.4 Efficient Clustering of Modules to Increase Safety of WSN

11.4.5 Point-to-Point Protection Approach

11.4.6 Registration and Key Management Phase

11.4.7 Secure Data Exchange Phase

11.4.8 Generating Perturb Phase

11.4.9 Signature and Perturbation Phase

11.4.10 Authentication Phase

11.4.11 Decryption and Authentication

11.5 Conclusion

References

Chapter 12 An Epileptic Seizure Detection and Classification Based on Machine Learning Techniques

12.1 Introduction

12.2 Related Work

12.3 Proposed Methodology

12.3.1 Database Description – BONN University EEG Dataset

12.3.2 Evaluation Assessment Method

12.3.3 Classification Techniques

12.4 Experimental Results

12.5 Discussion

12.6 Conclusion

References

Chapter 13 Analysis of Coronary Artery Disease Using Various Machine Learning Techniques

13.1 Introduction

13.2 Literature Survey

13.3 Material and Methods

13.3.1 Dataset Description

13.4 Methodology

13.4.1 Data Normalization

13.4.2 Logistic Regression

13.4.3 Types of Logistic Regression

13.5 Result Analysis

13.5.1 Performance Comparison of Algorithms

13.6 Discussion

13.7 Conclusion

References

Index

People also search for Next Generation Healthcare Systems Using Soft Computing Techniques 1st Edition:

next generation health technology
    
next generation healthcare patient portal
    
quality systems inc nextgen
    
quality systems nextgen
    
qsi nextgen healthcare

Tags: Rekh Ram Janghel, Rohit Raja, Korhan Cengiz, Hiral Raja, Next Generation, Healthcare Systems, Soft Computing Techniques