Medicine & Health Sciences

Integrating Biomedical Image Processing and Informatics for Healthcare
Editors: Nikita Jain, PhD
V. Dhilip Kumar, PhD
Oana Geman, PhD
Aryan Chaudhary, PhD

Integrating Biomedical Image Processing and Informatics for Healthcare

Now on Press
Pub Date: Forthcoming December 2026
Hardback Price: see ordering info
Hard ISBN: 9781779520593
E-Book ISBN: 9781779520609
Pages: 510 pages with
Binding Type: Hardback / ebook
Notes: 142 b/w illustrations

In today’s fast-paced and ever-changing world of 21stcentury healthcare, the blend of technology, data, and medicine is reshaping how we think about diagnosis, treatment, and patient care. At the heart of this change is the smooth integration of biomedical imaging, informatics, and artificial intelligence (AI)—a combination that’s not just improving clinical decision- making but also pushing us toward a more predictive, personalized, and preventive approach to healthcare. This new book, Integrating Biomedical Imaging and Informatics for AI-Driven Healthcare, showcases the latest advancements across the key areas of artificial intelligence in healthcare, data acquisition and processing, and emerging technologies such as the digital twin.

The volume first offers a comprehensive yet detailed overview of how AI is being applied in healthcare, delving into the roles of machine learning, deep learning, and federated learning in helping machines with clinical diagnostics, pattern recognition, patient monitoring, and decision support systems. It covers topics on continuous patient monitoring, smart imaging, and algorithm-driven diagnostics to showcase how computational power is enhancing and supporting medical expertise.

The roles of data acquisition and processing in healthcare are considered as well, looking at the various innovations in gathering, processing, and analyzing intricate biomedical datasets. It explores topics from cardiotocography used for monitoring fetuses to the fascinating world of transfer learning for detecting pneumonia through chest X-rays. The chapters showcase real-world applications of image processing and advanced computing techniques. The book also takes a closer look at cutting-edge technologies like generative adversarial networks (GANs), offering readers a glimpse into how synthetic data generation and image enhancement are helping to fill the gaps in data availability and improve diagnostic accuracy.

Digital twins and emerging technologies in healthcare is also introduced along with the applications across various healthcare settings. By harnessing real-time data from wearables, IoT devices, and imaging systems, digital twins hold incredible promise for tailoring treatment plans, monitoring health in real-time, and enabling proactive healthcare interventions. The book also highlights complementary technologies like nanotechnology-driven blood flow simulations, AI-enhanced athletic performance training, and IoT-integrated hospital systems, showcasing a range of futuristic, holistic approaches to healthcare.

What ties together all the contributions in this volume is a common vision for patient-centered, data-driven healthcare. In a world thats increasingly influenced by digital ecosystems, healthcare needs to shift from being reactive to becoming proactive and continuous—where diagnostics, monitoring, and interventions are guided by solid data, smart algorithms, and systems that work well together. The technologies and methods discussed here showcase this transformation, where machines enhance human care, and virtual simulations shape real-world outcomes.

CONTENTS:
Preface

PART I: ARTIFICIAL INTELLIGENCE IN HEALTHCARE
1. An Outline on AI
Abhishek Sharma

2. Exploring the Transformative Impact of Deep Learning in Healthcare
Harshita Virwani, Mohit Gupta, and Nikita Jain

3. An Introduction to Image Processing
Tushar Srivastava, Amit Kumar, and Sudharshan Mothukuru

4. A Comprehensive Study of Federated Learning: Research Challenges, Applications, and Future Directions
M. Manimaran and V. Dhilipkumar

5. Machine Learning Applications in Healthcare Diagnosis and Treatment
Almas Begum, Cyrilraj V., and Alex David

6. Pattern Classification in AI with Healthcare
Barkha Narang, Harshita Virwani, and Nikita Jain

7. Patient Monitoring Using AI
Ashish Kumar and Amit Kumar

8. Applications of Artificial Intelligence in Continuous Patient Monitoring
Hemalatha D., Suganya V., and Prema S.

9. Using AI to Addressing Medical Imaging
Geeta Tiwari, Sanjeev Kumar, and Neeraj Tiwari

PART II: DATA ACQUISITION AND PROCESSING IN HEALTHCARE
10. Classification of Fetal Health Rate from Cardiotocography Dataset Using Efficient Ensemble Learning Techniques: A Hard Computing Approach
R. Sofia, S. Yazhinian, and Saranya Jayapalan

11. Advancements in Video Deblurring Techniques for Biomedical Applications
Salini Abraham and Kanimozhi T.

12. Integrated Framework for Pneumonia Prediction from Chest X-Ray Images: Comparative Analysis of Machine Learning and Deep Learning Models Leveraging Transfer Learning Techniques
Monika Agarwal, Vinay R., Mohith N., Y. Chaitanya Shiva Srinivas, Nitisha S., and Mokshitha M.

13. A Problem-Based Learning Scenario of Generative Adversarial Networks (GANs) in Biomedical Imaging: From Theory to Practice
Oana Geman, Roxana Toderean, and Dragos Vicoveanu

PART III: DIGITAL TWINS AND EMERGING TECHNOLOGIES IN HEALTHCARE
14. A Novel Framework of Digital Twin in Healthcare
Prabh Deep Singh, Kiran Deep Singh, Surya Kant Sharma, and Kamlesh Gautam

15. IoT in Healthcare: Transforming Patient Monitoring
E. Kannan, Sriram Kannan, Carmel Mary, and Belinda M. J.

16. Exploring the Effects of Sport Activity on Human Health: Integrative Approaches in the Age of Medical Technology
Scheuleac Adelina, Vizitiu Elena, and Roxana Toderean

17. Casson MHD Blood Flow of Nano-Particles as an Implementation to Treatment of Cancer
Abhishek Neemawat and Nimit Jain

18. Utilization of Artificial Intelligence and Machine Learning Techniques in the Healthcare Sector for the Early Prediction of Breast Cancer Disease
Ram Babu Buri and Vishal Shrivastava

19. The Impact of Artificial Intelligence on the Training of Performance Athletes
Elena Vizitiu, Eduard Zadobrischi, and Roxana Toderean

Index


About the Authors / Editors:
Editors: Nikita Jain, PhD
Professor and Head of Department, Poornima College of Engineering, Jaipur, Rajasthan India

Nikita Jain, PhD, is Professor and Head of Department of Computer Engineering at Poornima College of Engineering, Jaipur, Rajasthan, India. She has more than 18 years of teaching experience as well as research experience. She has published in various international journals and international conferences in the field of computer science, machine learning, deep learning, and the healthcare sector. She is an editorial board member and reviewer for various international journals and conferences, such as Springer, Frontiers, MDPI, IGI Global, etc. Her area of interest is advanced computing and healthcare, machine learning, deep learning, etc. Dr. Jain is a seasoned academic with a passion for cutting-edge technology and healthcare innovation. She serves as the esteemed Treasurer of the Meerut ACM Professional Chapter, spearheading advancements in advanced computing, machine learning, deep learning, and their impactful applications in healthcare. She did her BTech and MTech in Computer Science and Engineering at UPTU, Lucknow and RTU Kota.

V. Dhilip Kumar, PhD
Professor and Associate Dean, School of Computing, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Chennai, India

V. Dhilip Kumar, is working as a Professor and Associate Dean in the School of Computing at Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Chennai, where he was previously Head of the Department of Artificial Intelligence and Data Science. He has more than 14 years of teaching and research experience He has published in various international journals and international conferences in the field of machine learning, deep learning, IoT, wireless communication, and vehicular communication. He is an editorial board member and reviewer for various international journals and conferences, such as Springer, Frontiers, MDPI, IGI Global etc. His area of interest is wireless communication, software-defined networks, Internet of things, machine learning and expert systems, etc. Currently he is working on a project funded by the Indian DBT on marine biotechnology in the field of precision aquaculture using machine learning. He is guiding several PhD scholars in the field of machine learning for healthcare, precision agriculture, and computer vision. He was awarded his PhD at North Eastern Hill University (A Central University of India) in 2018. He did his B inTech Information Technology and ME Computer Science Engineering under Anna University, Chennai. He completed his postdoctoral research fellowship with the collaboration of the University of Suceava and Green Soft, Lasi, Romania.

Oana Geman, PhD
Professor, University Stefan cel Mare of Suceava, Romania

Oana Geman, PhD, is currently an Associate Professor at the University of Suceava, Romania, and obtained Habilitation in the Electronics and Telecommunication field. She is a medical bioengineer and has a PhD in Electronics and Telecommunication and a post-doctoral research degree in Computer Science (2012). In the last five years, she has published 10 books, over 150 articles (100 articles in ISI Web of Science journals, 45 articles in ISI indexed conference volumes as main author, and over 20 papers in Q1and Q2 journals, with FI over 50), and her various works have been cited over 2600 times; her H-index is 28. She served as chair or organizer of many international conferences as well as session chair. She is a senior member of IEEE. She has been a director or a member in 10 national and international grants. Her current research interests include noninvasive measurements of biomedical signals, wireless sensors, signal processing, and processing information by way of artificial intelligence such as nonlinear dynamics analysis, stochastic networks and neuro-fuzzy methods, classification and prediction, data mining, deep learning, intelligent systems, bioinformatics and biostatistics, and biomedical applications. She is a reviewer and editor of many top journals, including IEEE Transactions, IEEE Access, IEEE Internet of Things Journal, Sensors, Symmetry, etc.

Aryan Chaudhary, PhD
Chief Scientific Advisor, BioTech Sphere Research, India

Aryan Chaudhary is the Chief Scientific Advisor at BioTech Sphere Research, India. He continues to make groundbreaking contributions to the industry. Having served as the Research Head at Nijji HealthCare Pvt Ltd, he has demonstrated his expertise in leveraging revolutionary technologies such as artificial intelligence, deep learning, IoT, cognitive technology, and blockchain to revolutionize the healthcare landscape. His relentless pursuit of excellence and innovation has earned him recognition as a thought leader in the industry. His dedication to advancing healthcare is evident through his vast body of work. He has authored several influential academic papers on public health and digital health, published in prestigious international journals. His research primarily focuses on integrating IoT and sensor technology for efficient data collection through one-time and ambulatory monitoring. As a testament to his expertise and leadership, he is not only a keynote speaker at numerous international and national conferences but also serves as a series editor of a CRC book series and is the editor of several books on biomedical science. His commitment to the advancement of scientific knowledge extends further, as he acts as a guest editor for special issues in renowned journals. Recognized for his significant contributions, he has received prestigious accolades, including the “Most Inspiring Young Leader in Healthtech Space 2022” by Business Connect and the title of the best project leader at Global Education and Corporate Leadership. Moreover, he holds senior memberships in various international science associations, reflecting his influence and impact in the field. Adding to his accomplishments, Aryan Chaudhary is currently serving as a guest editor for a special issue in the highly regarded journal, EAI Endorsed Transactions on AI and Robotics, and he has joined the editorial board of Biomedical Science and Clinical Research (BSCR). Additionally, he is a respected professional member of the Association for Computing Machinery (ACM). He has been appointed as a Technical Committee Member for the tenure 2024–2025 with the IEEE Robotics and Automation Society.




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