Application of Deep Learning Methods in Healthcare and Medical Science

325 Pages·2022·24.202 MB·English

by  Rohit Tanwar, Prashant Kumar, Malay Kumar, Neha Nandal

APPLICATION OF

DEEP LEARNING METHODS IN

HEALTHCARE AND MEDICAL SCIENCE

APPLICATION OF

DEEP LEARNING METHODS IN

HEALTHCARE AND MEDICAL SCIENCE

Edited by
Rohit Tanwar, PhD

Prashant Kumar, PhD

Malay Kumar, PhD

Neha Nandal, PhD
First edition published 2023
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Library and Archives Canada Cataloguing in Publication
Title: Application of deep learning methods in healthcare and medical science / edited by Rohit Tanwar, PhD,
Prashant Kumar, PhD, Malay Kumar, PhD, Neha Nandal, PhD.
Names: Tanwar, Rohit, editor. | Kumar, Prashant, 1986- editor. | Kumar, Malay, 1988- editor. | Nandal, Neha, 1990- editor.
Description: First edition. | Includes bibliographical references and index.
Identifiers: Canadiana (print) 20220285055 | Canadiana (ebook) 20220285071 | ISBN 9781774911204 (hardcover) |
ISBN 9781774911211 (softcover) | ISBN 9781003303855 (ebook)
Subjects: LCSH: Medical technology. | LCSH: Medical care—Technological innovations. | LCSH: Deep learning
(Machine learning)
Classification: LCC R855.3 .A66 2023 | DDC 610.285—dc23
Library of Congress Cataloging‑in‑Publication Data
Names: Tanwar, Rohit, editor. | Kumar, Prashant, 1986- editor. | Kumar, Malay, 1988- editor. | Nandal, Neha, 1990- editor.
Title: Application of deep learning methods in healthcare and medical science / edited by Rohit Tanwar, Prashant Kumar,
Malay Kumar, Neha Nandal.
Description: First edition. | Palm Bay, FL : Apple Academic Press, 2023. | Includes bibliographical references and index. |
Summary: “This volume provides a wealth of up-to-date information on developments and applications of deep learning
in healthcare and medicine. It aims to provide deep insight and understanding of novel applications that address the
tough questions of disease diagnosis, prevention, and immunization. The volume looks at applications of deep learning
for major medical challenges such as cancer detection and identification, birth asphyxia among neonates, kidney
abnormalities, white blood cell segmentation, diabetic retinopathy detection, and Covid-19 diagnosis, prevention, and
immunization. The volume discusses applications of deep learning in detection, diagnosis, intensive examination and
evaluation, genomic sequencing, convolutional neural networks for image recognition and processing, and more for
health issues such as kidney problems, brain tumors, lung damage, and breast cancer. The authors look at ML for brain
tumor segmentation, in lung CT scans, in digital X-Ray devices, and for a logistic and transport systems for effective
delivery of healthcare. Chapters include studies and discussions on chest X-ray images using CNN to identify Covid-19
infections, lung CT scan images using pre-trained VGG-16 and 3-layer CNN to distinguish Covid and non-Covid
patients, genomic sequencing to study the Covid virus, breast cancer identification using CNN, brain tumor detection
using multimodal image fusion and segmentation, factors responsible for birth asphyxia in neonates, and much more.
It also explores cancer identification and detection using deep learning methods in the human body through algorithms
based on issues, laboratory tests, imaging tests, biopsies, bone scans, computerized tomography scans, positron
emission tomography, and ultrasound. This volume, Application of Deep Learning Methods in Healthcare and Medical
Science, showcases the diverse applications of patient-based data collection and analysis in medicine and healthcare
using computer algorithms for effective health diagnosis, prevention, and patient care”-- Provided by publisher.
Identifiers: LCCN 2022031830 (print) | LCCN 2022031831 (ebook) | ISBN 9781774911204 (hardcover) | ISBN 9781774911211
(paperback) | ISBN 9781003303855 (ebook)
Subjects: MESH: Medical Informatics | Deep Learning
Classification: LCC R855.3 (print) | LCC R855.3 (ebook) | NLM W 26.55.A7 | DDC 610.285--dc23/eng/20220824
LC record available at https://lccn.loc.gov/2022031830
LC ebook record available at https://lccn.loc.gov/2022031831
ISBN: 978-1-77491-120-4 (hbk)
ISBN: 978-1-77491-121-1 (pbk)
ISBN: 978-1-00330-385-5 (ebk)
About the Editors

Rohit Tanwar, PhD
Associate Professor, School of Computer Sciences,

University of Petroleum and Energy Studies, Dehradun,

Uttarakhand, India, Tel.: [phone],

E-mail: [email protected]

Rohit Tanwar, PhD, is an Associate Professor at the School of Computer
Sciences, University of Petroleum and Energy Studies, Dehradun, India.
He has more than 10 years of experience in teaching. His areas of interests
include network security, optimization techniques, human computing, soft
computing, cloud computing, data mining, etc. Dr. Tanwar has published
several books in the domain of healthcare and security with reputed interna­
tional publishers. He is associated with some highly indexed international
journals as guest editor/onboard reviewer. He has more than 30 publica­
tions to his credit to date in reputed journals and conferences. He has been
associated with many conferences throughout India as member, session
chair, etc. He is supervising PhD research scholars in the fields of security
and optimization. Dr. Tanwar received his bachelor’s degree in CSE from
Kurukshetra University, Kurukshetra, India, and master’s degree in CSE
from YMCA University of Science and Technology, Faridabad, India. He
has received his PhD in CSE from Kurukshetra University, India.
Prashant Kumar, PhD
Assistant Professor, Department of Computer Science
and Engineering, Dr. BR Ambedkar National Institute of
Technology, Jalandhar, Punjab, India,
Tel.: [phone], E-mail: [email protected]
Prashant Kumar, PhD, is an Assistant Professor in the Department of
Computer Science and Engineering at the Dr. B. R. Ambedkar National
Institute of Technology, Jalandhar, India. Previously he has worked with
the Department of Systemics in the School of Computer Science at the
vi About the Editors
University of Petroleum and Energy Studies, Dehradun, India, and the
Department of Computer Science and Engineering at the National Institute
of Technology Hamirpur, India. His research interests include opportunistic
and delay-tolerant networks, device-to-device communications, wireless
and adhoc networks, and security in wireless networks. He has published
more than 25 research papers in journals and conferences of international
repute. He is a member of IEEE, International Association of Engineers,
and the Internet Society. Dr. Kumar received his PhD and MTech degrees
from the National Institute of Technology Hamirpur, India.
Malay Kumar, PhD
Assistant Professor, Department of Computer Science
and Engineering, Indian Institute of Information
Technology, Dharwad IT Park, Hubli, Karnataka,
India, Tel.: [phone],
E-mail: [email protected]
Malay Kumar, PhD, is an Assistant Professor in the Department of
Computer Science and Engineering at the Indian Institute of Information
Technology Dharwad, India. Earlier he was associated with the School
of Computer Science of the University of Petroleum and Energy Studies,
Dehradun, India. He has authored more than 20 research papers in inter­
national journals and conferences. His research areas of interest are appli­
cation of machine learning and deep learning in medical sciences, and
security and privacy issues in cloud computing. He has served as chair
and technical program committee member for numerous international
conferences and workshops. He was a guest editor of several international
journals and a lead editor of several books. Dr. Kumar earned his BTech
in Computer Science and Engineering from CSJM University Kanpur,
his MTech from NIT Kurukshetra, and his PhD from NIT Raipur, India.
About the Editors vii
Neha Nandal, PhD
Associate Professor, Department of Computer Science and
Engineering, Gokaraju Rangaraju Institute of Engineering
and Technology, Hyderabad, Telangana, India,
Tel.: [phone], E-mail: [email protected]
Neha Nandal, PhD, is an Associate Professor in the Computer Science
and Engineering Department of the Gokaraju Rangaraju Institute of Engi­
neering and Technology, Hyderabad, India. She has published 19 articles
in her research area in different journals and conferences, including
SCI- and SCOPUS-level journals. She is a life-time member of IETA.
Dr Neha has participated in different workshops; completed courses on
Python, machine learning, and deep learning on Coursera; and also hosted
different faculty development programs. Her research interests include
pattern recognition and machine learning. She earned her BTech in CSE
from the Technological Institute of Textile and Sciences, Bhiwani, and
her MTech in CSE from Amity University Jaipur, India, with distinction.
Recently, she has been awarded a PhD in Machine Learning.

Contents

Contributors ......................................................................................................... xi

Abbreviations .......................................................................................................xv

Preface ............................................................................................................... xix

1. A Review on Detection of Kidney Disease Using Machine

Learning and Deep Learning Techniques ................................................. 1

Vemu Santhi Sri, P. Sathish Kumar, and V. Rajendran
2. Deep Learning‑Based Computer‑Aided Diagnosis System ...................23

G. Vijaya
3. Extensive Study of WBC Segmentation Using

Traditional and Deep Learning Methods ............................................... 49

Chandradeep Bhatt, Indrajeet Kumar, Sandeep Chand Kumain, and

Jitendra Kumar Gupta

4. Introduction and Application of SVM in Brain Tumor

Segmentation ............................................................................................. 67

Amit Verma
5. Detection Analysis of COVID‑19 Infection Using the Merits of

Lungs CT Scan Images with Pre‑Trained VGG‑16 and

3‑Layer CNN Models ................................................................................79

P. Vijayalakshmi, P. Sathish Kumar, and V. Rajendran
6. Deep Learning Methods for Diabetic Retinopathy Detection ............. 101

Tahir Javed, Sheema Parwaz, and Janibul Bashir
7. Study to Distinguish Covid‑19 from Normal Cases Using

Chest X‑Ray Images with Convolution Neural Network .................... 121

P. Sathish Kumar, P. Vijayalakshmi, and V. Rajendran
8. Breast Cancer Classification Using CNN Extracted Features:
A Comprehensive Review .......................................................................147

Arpit Kumar Sharma, Amita Nandal, Todor Ganchev, and Arvind Dhaka