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Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development




ISBN 9780367257576
Published November 27, 2019 by Chapman and Hall/CRC
146 Pages - 24 B/W Illustrations

 
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Book Description

Healthcare sector is characterized by difficulty, dynamism and variety. In 21st century, healthcare domain is surrounded by tons of challenges in terms of Disease detection, prevention, high costs, skilled technicians and better infrastructure. In order to handle these challenges, Intelligent Healthcare management technologies are required to play an effective role in improvising patient’s life. Healthcare organizations also need to continuously discover useful and actionable knowledge to gain insight from tons of data for various purposes for saving lives, reducing medical operations errors, enhancing efficiency, reducing costs and making the whole world a healthy world.

Applying Swarm Intelligence and Evolutionary Algorithms in Healthcare and Drug Development is essential nowadays. The objective of this book is to highlight various Swarm Intelligence and Evolutionary Algorithms techniques for various medical issues in terms of Cancer Diagnosis, Brain Tumor, Diabetic Retinopathy, Heart disease as well as drug design and development. The book will act as one-stop reference for readers to think and explore Swarm Intelligence and Evolutionary Algorithms seriously for real-time patient diagnosis, as the book provides solutions to various complex diseases found critical for medical practitioners to diagnose in real-world.

Key Features:

  • Highlights the importance and applications of Swarm Intelligence and Evolutionary Algorithms in Healthcare industry.
  • Elaborates Swarm Intelligence and Evolutionary Algorithms for Cancer Detection.
  • In-depth coverage of computational methodologies, approaches and techniques based on Swarm Intelligence and Evolutionary Algorithms for detecting Brain Tumour including deep learning to optimize brain tumor diagnosis.
  • Provides a strong foundation for Diabetic Retinopathy detection using Swarm and Evolutionary algorithms.
  • Focuses on applying Swarm Intelligence and Evolutionary Algorithms for Heart Disease detection and diagnosis.
  • Comprehensively covers the role of Swarm Intelligence and Evolutionary Algorithms for Drug Design and Discovery.

The book will play a significant role for Researchers, Medical Practitioners, Healthcare Professionals and Industrial Healthcare Research and Development wings to conduct advanced research in Healthcare using Swarm Intelligence and Evolutionary Algorithms techniques.

Table of Contents

 CONTENTS

Preface, xi

About the Editors, xv

Contributors, xix

Abbreviations, xxi

CHAPTER 1 ■ Swarm Intelligence and Evolutionary

Algorithms in Disease Diagnosis—Introductory

Aspects 1

BHUSHAN INJE, SANDEEP KUMAR, AND ANAND NAYYAR

1.1 INTRODUCTION 1

1.2 TERMINOLOGIES 2

1.2.1 Swarm Intelligence 2

1.2.1.1 Merits of Swarm Intelligence 3

1.2.1.2 Classifications and Terminology 4

1.2.2 Evolutionary Computation 5

1.2.3 Evolutionary Computation Paradigms 6

1.3 IMPORTANCE OF SWARM INTELLIGENCE IN

DISEASE DIAGNOSIS 7

1.4 IMPORTANCE OF EVOLUTIONARY ALGORITHMS

IN DISEASE DIAGNOSIS 10

1.5 CONCLUSION 14

CHAPTER 2 ■ Swarm Intelligence and Evolutionary

Algorithms for Cancer Diagnosis 19

BANDANA MAHAPATRA AND ANAND NAYYAR

2.1 INTRODUCTION 19

2.2 CLASSIFICATION OF CANCER 21

2.3 CHALLENGES IN CANCER DIAGNOSIS 26

2.3.1 Methods of Cancer Detection 26

2.3.2 Issues and Challenges Faced While Cancer

Detection Process 27

2.4 APPLYING SWARM INTELLIGENCE ALGORITHM

FOR CANCER DIAGNOSIS 28

2.4.1 SI Algorithms for Detection of Lung Cancer 29

2.4.2 Swarm Intelligence for Breast Cancer 30

2.4.3 Swarm Intelligence for Ovarian Cancer 30

2.4.4 SI Algorithm for Early Detection of Gastro Cancer 30

2.4.5 Swarm Intelligence for Treating Nano-Robots 31

2.5 APPLYING EVOLUTIONARY ALGORITHM FOR

CANCER DETECTION 34

2.6 CONCLUSION 40

CHAPTER 3 ■ Brain Tumour Diagnosis 45

DHANANJAY JOSHI, NITIN CHOUBEY, AND RAJANI KUMARI

3.1 INTRODUCTION 45

3.2 APPLYING EVOLUTIONARY ALGORITHMS FOR

BRAIN TUMOR DIAGNOSIS 50

3.2.1 Evolutionary Algorithm 50

3.2.2 Conceptual Framework 1: Applying Evolutionary

Algorithm for Brain Tumor Diagnosis. 52

3.3 APPLYING SWARM INTELLIGENCE ALGORITHMS

FOR BRAIN TUMOR DIAGNOSIS 54

3.3.1 Swarm Intelligence (SI) - Based Algorithms 54

3.3.2 Self-Organization: 55

3.3.3 Division of Labor: 55

3.3.4 Particle Swarm Optimization 55

3.3.5 Particle Swarm Optimization Algorithm 56

3.3.6 Conceptual Framework 2: Applying Swarm

Intelligence Based Algorithm for Brain Tumor

Diagnosis 57

3.4 APPLYING SWARM INTELLIGENCE AND

EVOLUTIONARY ALGORITHMS TOGETHER FOR

DIAGNOSIS OF BRAIN TUMOR 58

3.5 APPLYING SWARM INTELLIGENCE, EVOLUTIONARY

ALGORITHM AND INCORPORATING TOPOLOGICAL

DATA ANALYSIS (TDA) FOR BRAIN TUMOR

DIAGNOSIS 59

3.5.1 Topological Data Analysis 59

3.6 CONCLUSION 59

CHAPTER 4 ■ Swarm Intelligence and Evolutionary

Algorithms for Diabetic Retinopathy

Detection 65

SACHIN BHANDARI, RADHAKRISHNA RAMBOLA, AND RAJANI KUMARI

4.1 INTRODUCTION 65

4.1.1 Classification of Diabetic Retinopathy 66

4.1.2 Swarm Optimization and Evolutionary

Algorithms 69

4.1.3 Objectives and Contributions 71

4.2 FEATURE OF DIABETIC RETINOPATHY 72

4.2.1 Microaneurysms 72

4.2.2 Haemorrhages 73

4.2.3 Hard Exudates 73

4.2.4 Soft Exudates 73

4.2.5 Neo-Vascularization 74

4.2.6 Macular Edema 74

4.3 DETECTION OF DIABETIC RETINOPATHY BY

APPLYING SWARM INTELLIGENCE AND

EVOLUTIONARY ALGORITHMS 74

4.3.1 Genetic Algorithm 75

4.3.2 Particle Swarm Optimization 79

4.3.3 Ant Colony Optimization 81

4.3.4 Cuckoo Search 84

4.3.5 Bee Colony Optimization 85

4.4 CONCLUSION 87

CHAPTER 5 ■ Swarm Intelligence and Evolutionary

Algorithms for Heart Disease Diagnosis 93

RAJALAKSHMI KRISHNAMURTHI

5.1 INTRODUCTION 93

5.2 PREDICTION AND CLASSIFICATION OF HEART

DISEASE USING MACHINE LEARNING/SWARM

INTELLIGENCE 95

5.2.1 Decision Support System 95

5.2.2 Clinical Decision Support System 96

5.2.3 Heart Disease Datasets 97

5.3 PREDICTING HEART ATTACKS IN PATIENTS

USING ARTIFICIAL INTELLIGENCE METHODS

(FUZZY LOGIC) 98

5.3.1 Fuzzy Logic Approach for Heart Disease Diagnosis 99

5.3.2 Fuzzy Rule Base 101

5.3.3 Fuzzy Inference Engine 102

5.3.4 Defuzzification 102

5.4 PREDICTING HEART DISEASE USING GENETIC

ALGORITHMS 103

5.5 SWARM INTELLIGENCE BASED OPTIMIZATION

PROBLEM FOR HEART DISEASE DIAGNOSIS 105

5.5.1 Ant Colony Optimization 105

5.5.2 Particle Swarm Optimization 106

5.6 HEART DISEASE PREDICTION USING DATA MINING

TECHNIQUES 108

5.7 PERFORMANCE METRICS 110

5.8 CONCLUSION 113

CHAPTER 6 ■ Swarm Intelligence and Evolutionary

Algorithms for Drug Design and

Development 117

BANDANA MAHAPATRA

6.1 INTRODUCTION 117

6.2 DRUG DESIGN AND DEVELOPMENT: PAST, PRESENT

AND FUTURE 119

6.3 ROLE OF SWARM INTELLIGENCE IN DRUG DESIGN

AND DEVELOPMENT 123

6.4 ROLE OF EVOLUTIONARY ALGORITHMS IN DRUG

DESIGN AND DEVELOPMENT 126

6.5 QSAR MODELLING USING SWARM INTELLIGENCE

AND EVOLUTIONARY ALGORITHMS 128

6.6 PREDICTION OF MOLECULE ACTIVITY SWARM

INTELLIGENCE AND EVOLUTIONARY ALGORITHMS 131

6.6.1 Particle Swarm Optimization 135

6.7 CONCLUSION 136

INDEX, 141

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Editor(s)

Biography

About the Editors

Sandeep Kumar is currently an Assistant Professor of

Computer Science & Engineering at Amity University

Rajasthan, Jaipur, India. Dr. Kumar holds a PhD

degree in Computer Science & Engineering, M. Tech.

degree from RTU, Kota, BE degree from Engineering

College, Kota. Dr. Kumar was Assistant Professor of

Computer Science & Engineering at ACEIT, Jaipur, 2008–2011, and

Assistant Professor of Computer Science, Faculty of Engineering &

Technology, Jagannath University, Jaipur, 2011–2017. Dr. Kumar was

the head of computer science at Jagannath University, 2013–2017. He is

also working as guest editor for special issue of many journals including

Int. J. of Intelligent Information and Database Systems (IJIIDS), Int. J. of

Agricultural Resources, Governance and Ecology (IJARGE), Int. J. of

Environment and Sustainable Development (IJESD), Inderscience, Recent

Patents on Computer Science, Bentham Science, and member of editorial

boards for many international journals, and member of technical program

committees of many conferences. He has delivered many keynote

and expert talks in national/international conferences/workshop. He is

also reviewer in many international journals and conferences, and acts

as chairperson in many conferences. Dr. Kumar has over 50 publications

in well-known SCI/SCOPUS indexed international journals and conferences,

and has attended several national and international conferences

and workshops. He has authored/edited four books in the area of

computer science. His research interests include Nature Inspired Algorithms,

Swarm Intelligence, Soft Computing and Computational

Intelligence.

 

Anand Nayyar received a PhD degree in Computer

Science from Desh Bhagat University in Mandi Gobindgarh.

Currently, he is working as Lecturer, Researcher and

Scientist at the Graduate School at Duy Tan University,

Vietnam. He has 15+ years of academic teaching experience

with more than 300 publications in reputed international

conferences, journals and book chapters (indexed

By: SCI, SCIE, Scopus, DBLP). Dr. Nayyar is a certified

professional with more than 75 certifications from various IT companies like:

CISCO, Microsoft, Oracle, Cyberoam, GAQM, Beingcert.com, ISQTB, EXIN,

Google and many more. His areas of interest include: Wireless Sensor

Networks, MANETS, Cloud Computing, Network Security, Swarm Intelligence,

Machine Learning, Network Simulation, Ethical Hacking, Forensics,

Internet of Things (IoT), Big Data, Linux and Open Source and Next

Generation Wireless Communications. In addition, Dr. Nayyar is

a Programme Committee Member/Technical Committee Member/Reviewer

for more than 400 international conferences to date. He has published 30

books in Computer Science by various National and International Reputed

Publishers like CRC Press, Elsevier, Springer, IGI-Global, BPB Publications,

Scholar Press, GRIN etc. He has received 20 awards for teaching and research,

including Young Scientist, Best Scientist, Exemplary Educationist, Young

Researcher and Outstanding Reviewer Award. He is acting as Associate

Editor of IGI-Global Journal - International Journal of Information Security

and Privacy (IJISP), International Journal of Distributed Systems and Technologies

(IJDST), International Journal of Cognitive Informatics and Natural

Intelligence (IJCINI), and International Journal of Green Computing (IJGC).

He is acting as Editor-in-Chief of IGI-Global Journal “International Journal

of Smart Vehicles and Smart Transportation (IJSVST)”.

 

Anand Paul is currently working in The School of

Computer Science and Engineering, Kyungpook

National University, South Korea, as Associate Professor.

He got his Ph.D. degree in electrical engineering at

National Cheng Kung University, Taiwan, R.O.C., in

2010. His research interests include Algorithm and Architecture Reconfigurable

Embedded Computing. He is a delegate representing South

Korea for M2M focus group and for MPEG. In 2004–2010 he has

been awarded Outstanding International Student Scholarship, and in

2009, 2015 he won the best paper award in national computer

Symposium, in Taipei, Taiwan, and international conference on Soft

computing and network security, India.

He has guest-edited various international journals and he is also

part of editorial team for Journal of Platform Technology. He serves

as a reviewer for various IEEE Transactions on Circuits and Systems

for Video Technology, IEEE Transactions on System, Man and Cybernetics,

IEEE Sensors, ACM Transactions on Embedded Computing

Systems, IET Image Processing, IET Signal Processing and IET Circuits

and Systems. He gave invited talk in International Symposium on

Embedded Technology workshop in 2012, He is the track chair for

Smart human computer interaction in ACM SAC 2015, 2014. He is

also an MPEG Delegate representing South Korea.