HealthTech Horizons

HealthTech Horizons
Charting the Future of Smart Healthcare Innovations, Deepfake and Metaverse

Biomedical Engineering

HealthTech Horizons
Charting the Future of Smart Healthcare Innovations, Deepfake and Metaverse Forthcoming

Editors:
Saurav Mallik, University of Arizona, Tucson, AZ, USA
Soumita Seth, Future Institute of Engineering and Management, Narendrapur, Kolkata, West Bengal, India
Ben Othman Soufiene,PRINCE Laboratory Research, ISITcom, Hammam Sousse,University of Sousse, Tunisia, Tunisie.

ISBN: 9788743809913 (Hardback) e-ISBN: 9788743809906

Available: September 2026


HealthTech Horizons provides a concise yet comprehensive view of how cutting-edge technologies are transforming healthcare. Covering AI and machine learning in diagnostics, deep learning architectures (CNNs, RNNs, GANs) for genomics and imaging, synthetic data augmentation, and optimization algorithms (MRMR, EHO, HHWO) for complex biomedical datasets, this book bridges research with real-world applications.

 

It also examines the disruptive rise of deepfake technologies and the metaverse in telemedicine, surgical training, and immersive patient care, while addressing the ethical and computational challenges of integrating these tools responsibly. Designed for researchers, clinicians, and innovators, HealthTech Horizons is both a technical reference and a roadmap for the next era of smart, ethical, and intelligent healthcare systems.

 

The digital revolution in healthcare is no longer on the horizon—it’s here. HealthTech Horizons dives deep into the convergence of biomedical science and advanced computational techniques, offering a research-driven perspective on how technology is redefining modern medicine. This book explores:

 

  • Artificial intelligence and machine learning in diagnostics, treatment planning, and personalized medicine.
  • Deep learning architectures (CNNs, RNNs, GANs) applied to genomics, medical imaging, and biomarker discovery.
  • Synthetic data augmentation and generative adversarial networks (GANs) for enhancing predictive accuracy.
  • Feature selection and optimization algorithms (e.g., MRMR, EHO, HHWO) for high-dimensional biomedical datasets.
  • Deepfake technologies and their dual role in healthcare innovations and security threats.
  • Metaverse applications in telemedicine, surgical simulation, and immersive patient care.
  • Ethical and computational challenges in deploying AI responsibly in clinical practice.

 

Bridging research and practice, this book is an indispensable resource for data scientists, bioinformaticians, clinicians, and healthcare innovators seeking to understand—and shape—the next frontier of smart healthcare systems. HealthTech Horizons is not just about the future; it is a roadmap for leveraging algorithms, data, and virtual ecosystems to create resilient, ethical, and intelligent healthcare solutions.

Keywords: Artificial intelligence (AI) in healthcare, machine learning for medicine, deep learning (CNN, RNN, GAN), healthcare data science, genomics and bioinformatics, biomarker discovery, feature selection (MRMR, EHO, HHWO), optimization algorithms in biomedicine, synthetic data generation, generative adversarial networks (GANs), medical image analysis, predictive modeling in healthcare, smart healthcare systems, digital health technologies, deepfake in healthcare, metaverse in medicine, telemedicine and virtual care, surgical simulation and training, ethical AI in healthcare, future of healthcare innovation

Chapter 1. Introduction: Fundamentals of HealthTech – Horizons with Smart Healthcare Innovations, Deepfake and the Metaverse

Chapter 2. Health Digital Twins: A New Era in Healthcare

Chapter 3. Exploring Deepfake Technology in Healthcare: Innovations, Applications, and Challenges

Chapter 4. Regulatory Frameworks and Ethics in Smart Healthcare Innovations: Deepfakes and the Metaverse

Chapter 5. Emergency Response Training in Metaverse Scenarios

Chapter 6. Orchestrating Healing Harmonies: The Sublime Confluence of Artificial Intelligence and Healthcare

Chapter 7. Hybrid Optimization Techniques for Gene Expression Analysis: The EHOSVM Paradigm

Chapter 8. Decoding Breast Cancer: Unleashing RNA-Seq Insights with Advanced Deep Learning and Modified WOA

Chapter 9. A Smart Healthcare Innovation for Detecting Colorectal Cancer through the Integration of ADAM Optimizer and Categorical Cross-Entropy Loss Function-based CNN Method

Chapter 10. Optimizing Heart Disease Prediction through Machine Learning and Synthetic Data Augmentation Using GANs

Chapter 11. GWF Algorithm for Image Forgery Detection