Table Of ContentData Science for Effective
Healthcare Systems
Data Science for Effective Healthcare Systems has a prime focus on the importance of
data science in the healthcare domain. Various applications of data science in the health-
care domain have been studied to find possible solutions. In this period of the C OVID-19
pandemic, data science and allied areas play a vital role in dealing with various aspects of
healthcare. Image processing, detection and prevention from the COVID-19 virus, drug
discovery, early prediction, and prevention of diseases are some thrust areas where data
science has proven to be indispensable.
Key Features
The book offers comprehensive coverage of the most essential topics, including:
• Big Data Analytics, Applications and Challenges in Healthcare
• Descriptive, Predictive and Prescriptive Analytics in Healthcare
• Artificial Intelligence, Machine Learning, Deep Learning and IoT in Healthcare
• Data Science in Covid-19, Diabetes, Coronary Heart Diseases, Breast Cancer, and
Brain Tumor
The aim of this book is to provide the future scope of these technologies in the healthcare
domain. This book will surely benefit research scholars, persons associated with health-
care, faculty, research organizations, and students to get insights into these emerging tech-
nologies in the healthcare domain.
Chapman and Hall/CRC Internet of Things:
Data-Centric Intelligent Computing,
Informatics, and Communication
The role of adaptation, machine learning, computational Intelligence, and data analytics in
the field of IoT Systems is becoming increasingly essential and intertwined. The capability
of an intelligent system is growing depending on various self-decision-making algorithms
in IoT Devices. IoT-based smart systems generate a large amount of data that cannot be
processed by traditional data processing algorithms and applications. Hence, this book
series involves different computational methods incorporated within the system with the
help of Analytics Reasoning, learning methods, Artificial intelligence, and Sense-making
in Big Data, which is most concerned in IoT-enabled environment.
This series focuses to attract researchers and practitioners who are working in Information
Technology and Computer Science in the field of intelligent computing paradigm, Big Data,
machine learning, Sensor data, Internet of Things, and data sciences. The main aim of
the series is to make available a range of books on all aspects of learning, analytics and
advanced intelligent systems and related technologies. This series will cover the theory,
research, development, and applications of learning, computational analytics, data process-
ing, machine learning algorithms, as embedded in the fields of engineering, computer sci-
ence, and Information Technology.
Series Editor:
Souvik Pal
Sister Nivedita University, (Techno India Group), Kolkata, India
Dac-Nhuong Le
Haiphong University, Vietnam
Security of Internet of Things Nodes: Challenges, Attacks, and Countermeasures
Chinmay Chakraborty, Sree Ranjani Rajendran and Muhammad Habib Ur Rehman
Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective
Meenu Gupta, Rachna Jain, Arun Solanki and Fadi Al-Turjman
Cloud IoT Systems for Smart Agricultural Engineering
Saravanan Krishnan, J Bruce Ralphin Rose, NR Rajalakshmi, N Narayanan Prasanth
Data Science for Effective Healthcare Systems
Hari Singh, Ravindara Bhatt, Prateek Thakral and Dinesh Chander Verma
Data Science for Effective
Healthcare Systems
Edited by
Hari Singh
Ravindara Bhatt
Prateek Thakral
Dinesh Chander Verma
First edition published 2023
by CRC Press
6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742
and by CRC Press
4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN
CRC Press is an imprint of Taylor & Francis Group, LLC
© 2023 selection and editorial matter, [Hari Singh, Ravindara Bhatt, Prateek Thakral and Dinesh Chander Verma];
individual chapters, the contributors
Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot
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Library of Congress Cataloging-in-Publication Data
Names: Singh, Hari, 1957- editor.
Title: Data science for effective healthcare systems / edited by Hari
Singh, Ravindara Bhatt, Prateek Thakral, Dinesh Chander Verma.
Description: First edition. | Boca Raton : Chapman & Hall/CRC Press, [2023]
| Series: Internet of things: data-centric intelligent computing,
informatics, and communication | Includes bibliographical references and
index. | Identifiers: LCCN 2022003644 (print) | LCCN 2022003645 (ebook) |
ISBN 9781032105680 (hardback) | ISBN 9781032307503 (paperback) |
ISBN 9781003215981 (ebook)
Subjects: LCSH: Medicine—Data processing. | Medical informatics. |
Medicine—Information technology.
Classification: LCC R858 .D3779 2023 (print) | LCC R858 (ebook) | DDC
610.285—dc23/eng/20220401
LC record available at https://lccn.loc.gov/2022003644
LC ebook record available at https://lccn.loc.gov/2022003645
ISBN: 9781032105680 (hbk)
ISBN: 9781032307503 (pbk)
ISBN: 9781003215981 (ebk)
DOI: 10.1201/9781003215981
Typeset in Palatino
by codeMantra
Contents
Preface ............................................................................................................................................vii
Editors ..............................................................................................................................................ix
1. Big Data in Healthcare: Applications and Challenges ...................................................1
Monika, Pradeep Kumar, and Sanjay Tyagi
2. Impact Analysis of COVID-19 on Different Countries: A Big Data Approach .......15
Reema Lalit and Nitin Sharma
3. Overview of Image Processing Technology in Healthcare Systems ..........................25
Ankit Singh and Sivanesan Dhandayuthapani
4. Artificial Intelligence to Fight against COVID-19 Coronavirus in Bharat ...............37
Pushpendra Kumar Verma and Preety
5. Classification-Based Prediction Techniques Using ML: A Perspective for
Health Care ............................................................................................................................43
Meenakshi Malik, Aditi Kaushik, and Rekha Khatana
6. Deep Learning for Drug Discovery: Challenges and Opportunities ........................57
Aarti
7. Issues and Challenges Associated with Machine Learning Tools for Health
Care System ...........................................................................................................................69
Parul Chhabra and Pradeep Kumar Bhatia
8. R eal-Time Data Analysis of COVID-19 Vaccination Progress Over the World ......79
Bijan Paul, Aditi Roy, Khan Raqib Mahmud, and Mohammad Rifat Rashid
9. Descriptive, Predictive, and Prescriptive Analytics in Healthcare ............................89
Kalimullah Lone and Shabir Ahmad Sofi
10. IoT Enabled Worker Health, Safety Monitoring and Visual Data Analytics ........105
Selvaraj Kesavan, Subhash Almel, and B.S. Muralidhar
11. Prevalence of Nomophobia and Its Association with Text Neck Syndrome
and Insomnia in Young Adults during COVID-19 .....................................................117
Richa Hirendra Rai, Vishal Mehta, Pallavi, and Sachindra Pratap Singh
12. The Role of AI, Fuzzy Logic System in Computational Biology and
Bioinformatics .....................................................................................................................133
A.H.M. Shahariar Parvez, Sadiq Iqbal, Subrato Bharati, Prajoy Podder,
Pinto Kumar Paul, and Aditya Khamparia
v
vi Contents
13. Analysis for Early Prediction of Diabetes in Healthcare Using Classification
Techniques ...........................................................................................................................149
Navneet Verma, Sukhdip Singh, and Devendra Prasad
14. Nomenclature of Machine Learning Algorithms and Their Applications ............161
Ritu Aggarwal and Suneet Kumar
15. Breast Cancer Prognosis Using Machine Learning Approaches ..............................169
Nadeem Yousuf Khanday and Shabir Ahmad Sofi
16. Machine L earning-Based Active Contour Approach for the Recognition of
Brain Tumor Progression ..................................................................................................183
Amit Chopra, Dinesh C. Verma, and Rajneesh Gujral
17. A Deep Neural N etworks-Based C ost-Effective Framework for Diabetic
Retinopathy Detection.......................................................................................................199
Pawan Kumar Upadhyay, Siddharth Batra, and Sunny Dhama
Index .............................................................................................................................................213
Preface
This book primarily introduces the importance of data science in the field of healthcare.
Data science has proven to be a gamechanger in the optimization of disease preven-
tion, drug discovery, diagnosis, treatment, hospital operation, and post-care monitoring.
Initially, the basic concepts, applications, and challenges related to data science will be
covered to lay down a strong foundation for its importance in healthcare. A large vol-
ume of data is generated in healthcare in processes primarily from clinical trials, genetic
information, electronic medical records (EMRs), billing, wearable data, care management
databases, scientific articles, social media, and internet research. A global pandemic like
COVID-19 has dramatically increased the need and the importance of data science and
analytics.Data science in healthcare industry is mainly used for predictive analysis that
uses artificial intelligence, machine learning, deep learning to predict possibility of an
event occurring in the future based on known present variables and facts. The various
available and emerging tools and techniques to manage this voluminous healthcare data
results in improving patient outcomes and reduce healthcare costs. Various techniques
such asregression and classification have been covered here for better insights into health-
care data analysis and its related advantages. This book also focuses on the importance of
visual analytics to observe the medical history of a patient for further courses of action to
cure the diseases. This book is also meant to enlighten the importance of data science in
drug discovery, pandemic like COVID-19 needs fast simulation techniques to observe the
reaction of drugs inthe body so that the drug can be approved by competent authorities
and used to cure the disease.
In nutshell, the tools and techniques of data science have changed the way to man-
age, analyze, and leverage healthcare data for better and optimized prediction.The main
motive of this book is to bring the research and findings together for clear directions for
future work.
vii
Editors
Dr Hari Singh has been an Assistant Professor ( Senior Grade) in
the Department of Computer Science and Engineering and
Information Technology at Jaypee University of Information
Technology, Solan, HP, India since 2018. He has a PhD, MTech and
B.Engg.( Honors) in Computer Science and Engineering. He earned
his PhD degree from Thapar University, Patiala, Punjab, India in
2017. He has more than twenty years of teaching experience that
includes significant administrative and research experience. His
areas of interest are Databases, Data Science, Big Data Analytics,
Distributed and Parallel Computing, Grid Computing, Cloud
Computing, and Machine Learning. He has many awards, honors, and recognitions to his
credit. He delivered several invited/ expert talks on recent research topics at renowned
institutes and universities. He has published several research papers in SCI/ Scopus,
peer-reviewed International Journals and book chapters. He has also presented and pub-
lished many research papers in National/ International Conferences. Dr Singh has also
worked as an editor of proceedings of various International/ National Conferences. He has
attended/ participated in several workshops at reputed Institutes/ Universities/
Organizations. He has organized several Conference/ Seminar/ Workshops. He has super-
vised Post Graduate Thesis/ Dissertations and handled an AICTE sponsored research
project under the RPS scheme and one consultancy project. He has been a member of
professional societies, such as CSI, ISTE, IEEE, and has been a member/ reviewer of several
Scopus-Indexed journals.
Dr Ravindara Bhatt is an Associate Professor in the Department of
Computer Science and Engineering and Information Technology
at Jaypee University of Information Technology, Waknaghat,
India. Ravindara joined the Department of Computer Science
and Engineering and Information Technology, Jaypee University
of Information Technology, in 2006. Ravindara earned his PhD
degree from Indian Institute of Technology, Kharagpur. Dr
Ravindara has over 20 years of extensive experience in Academics
and Industry. His areas of interest are Data Science, Big Data,
Machine Learning, and Wireless Sensor Networks. He has pub-
lished several research papers in SCI/ Scopus, peer-reviewed
International Journals. He has also presented and published
many research papers in National/ International Conferences and is a reviewer for various
renowned International journals.
ix
