Integrating Biomedical Image Processing and Informatics for Healthcare

1. Auflage 2026
ISBN: 978-1-77952-059-3
Verlag: Apple Academic Press

Buch, Englisch, 510 Seiten, Format (B × H): 152 mm x 229 mm

In the era of digital healthcare, the convergence of biomedical imaging, informatics, and artificial intelligence (AI) is transforming the way diseases are detected, diagnosed, monitored, and treated. This informative volume explores the latest advances driving this evolution, demonstrating how intelligent technologies are enabling more accurate diagnostics, personalized therapies, and data-driven clinical decision-making.

The volume examines the expanding role of AI in healthcare, including machine learning, deep learning, federated learning, and intelligent decision support systems. It highlights innovations in continuous patient monitoring, smart imaging, pattern recognition, and algorithm-assisted diagnostics, illustrating how computational methods complement clinical expertise. The book also explores advances in biomedical data acquisition and processing, with applications ranging from cardiotocography and chest X-ray analysis to transfer learning, image enhancement, and generative adversarial networks for synthetic medical data.

Emerging technologies receive equal attention, particularly the growing role of digital twins in personalized medicine. By integrating real-time data from medical imaging, wearable sensors, and IoT-enabled devices, digital twins offer new opportunities for predictive modeling, individualized treatment planning, and proactive patient care.

Zielgruppe

Academic and Postgraduate

Autoren/Hrsg.

Jain, Nikita

Kumar, V. Dhilip

Geman, Oana

Chaudhary, Aryan

Fachgebiete

• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie Medizinische Biotechnologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Bildgebende Verfahren, Nuklearmedizin, Strahlentherapie Radiologie, Bildgebende Verfahren

Inhaltsverzeichnis

Preface PART I: ARTIFICIAL INTELLIGENCE IN HEALTHCARE 1. An Outline on AI 2. Exploring the Transformative Impact of Deep Learning in Healthcare 3. An Introduction to Image Processing 4. A Comprehensive Study of Federated Learning: Research Challenges, Applications, and Future Directions 5. Machine Learning Applications in Healthcare Diagnosis and Treatment 6. Pattern Classification in AI with Healthcare 7. Patient Monitoring Using AI 8. Applications of Artificial Intelligence in Continuous Patient Monitoring 9. Using AI to Address Medical Imaging 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 11. Advancements in Video Deblurring Techniques for Biomedical Applications 12. Integrated Framework for Pneumonia Prediction from Chest X-Ray Images: Comparative Analysis of Machine Learning and Deep Learning Models Leveraging Transfer Learning Techniques 13. A Problem-Based Learning Scenario of Generative Adversarial Networks (GANs) in Biomedical Imaging: From Theory to Practice PART III: DIGITAL TWINS AND EMERGING TECHNOLOGIES IN HEALTHCARE 14. A Novel Framework of Digital Twin in Healthcare 15. IoT in Healthcare: Transforming Patient Monitoring 16. Exploring the Effects of Sport Activity on Human Health: Integrative Approaches in the Age of Medical Technology 17. Casson MHD Blood Flow of Nano-Particles as an Implementation to Treatment of Cancer 18. Utilization of Artificial Intelligence and Machine Learning Techniques in the Healthcare Sector for the Early Prediction of Breast Cancer Disease 19. The Impact of Artificial Intelligence on the Training of Performance Athletes Index

Über Autor(innen)

Nikita Jain, PhD, is Associate Professor of Computer Engineering at Poornima College of Engineering, Jaipur, India. Her research spans machine learning, deep learning, advanced computing, and AI applications in healthcare. She has more than 18 years of teaching and research experience and serves as an editor and reviewer for leading international journals.

V. Dhilip Kumar, PhD, is Professor and Associate Dean at Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Chennai, India. His research focuses on machine learning, IoT, intelligent systems, and healthcare applications. He has published extensively, leads funded research projects, and supervises doctoral research in AI and computer vision.

Oana Geman, PhD, is Associate Professor at the University of Suceava, Romania. A medical bioengineer, she specializes in biomedical signal processing, artificial intelligence, wireless sensors, and intelligent healthcare systems. She has authored more than 150 publications, serves on numerous editorial boards, and is a senior member of IEEE.

Aryan Chaudhary is Chief Scientific Advisor at BioTech Sphere Research, India. His work centers on artificial intelligence, digital health, IoT, blockchain, and emerging healthcare technologies. An active contributor to international scientific organizations, he has received recognition for innovation and leadership in health technology.