1st Edition
AI-Integrated Biosensors and Technologies for Automated Disease Detection and Drug Delivery Revolutionizing the Healthcare Industry
The book presents a comprehensive overview of biosensors, AI-integrated biosensor technologies, and their potential to enhance healthcare outcomes. It covers various types of biosensors and their principles and applications in disease diagnosis and drug delivery.
AI-Integrated Biosensors and Technologies for Automated Disease Detection and Drug Delivery System: Revolutionizing Healthcare Industry describes how biosensors can be used to detect diseases like cancer, infectious disease, cardiovascular disease, respiratory disease, metabolic disease, autoimmune disease, and uncommon disorders. It also encompasses drug delivery biosensors such as implantable biosensors, wearable biosensors, smart pills, and biosensors for personalized medicine. The book showcases the remarkable convergence of these fields, demonstrating the immense potential for breakthroughs in biosensors, biotechnology, AI-equipped sensors, IoT-controlled sensors, wireless-monitored sensors, and transformative applications by inviting readers to envision a future of smart healthcare ecosystems, inspiring them to embrace the possibilities and limitless horizons of this AI-powered era.
This book is intended for specialists, analysts, engineers, researchers, academics, professionals, and students working in biosensors and AI-integrated biosensor technologies to resolve the challenging issues associated with the leveraging of combating the fields of healthcare and medicine.
Chapter 1. Introduction to Artificial Intelligence (AI)-Integrated Biosensors
Chapter 2. Electrochemical Biosensors for Disease Detection
Chapter 3. Optical Biosensors for Medical Diagnostics
Chapter 4. Transforming Healthcare with Piezoelectric AI-Biosensors
Chapter 5. Wearable Biosensors for Continuous Health Monitoring
Chapter 6. Implantable Biosensors for Drug Delivery
Chapter 7. Leveraging Reinforcement Learning for Enhanced Cancer Detection
Chapter 8. Smartphone-Based Biosensors for At-Home Diagnostics
Chapter 9. Artificial Intelligence (AI) Techniques for Biosensor Data Analysis
Chapter 10. Cloud-Based Infrastructure for Connected Biosensors
Chapter 11. Machine Learning for Biosensor Signal Processing
Chapter 12. Smart Pills and Biosensors for Drug Delivery
Chapter 13. Biosensor Manufacturing and Commercialization
Chapter 14. Regulatory Landscape for AI-Based Medical Devices
Chapter 15. Precision Medicine Applications of AI-Integrated Biosensors
Chapter 16. Early Disease Detection with Multimodal Biosensors
Chapter 17. Bioinspired Design of Smart Biosensing Systems
Chapter 18. Ethics of Artificial Intelligence (AI) and Biosensors in Healthcare
Chapter 19. Biosensor-Based Monitoring of Treatment Efficacy
Chapter 20. Automated Interventions Driven by Biosensor Data
Chapter 21. The Future of AI-Enabled Automated Sensing and Therapy
Chapter 22. AI-Powered Precision Revolutionizing Disease Detection and Patient Care in Healthcare
Chapter 23. Applications and Challenges of Cybersecurity in Healthcare Medical Devices in Hospitals
Chapter 24. Cybersecurity for Internet of Things (IoT) Devices and Sensors
Chapter 25. Attacks in Internet of Things (IoT) Healthcare Wearable Sensors
Chapter 26. Conclusions and Outlook
Biography
Dr Alex Khang has over 28 years of teaching and research experience in information technology. He is a professor in information technology, AI, and data science. He is also a software industry expert and the Chief of Technology at the AI and Data Science Research Center at the Global Research Institute of Technology and Engineering, North Carolina, United States.
Dr Ushaa Eswaran is a Principal and Professor, Indira Institute of Technology and Sciences, Markapur, Andhra Pradesh, India. She is an academician with over 33 years of experience in education, research, skill development and career research.
