Revolutionizing Digital Healthcare Through Artificial Intelligence and Automation

Principles, Technologies, and Applications
Herausgeber: Khang, Alex

• Broschiertes Buch

Produktbeschreibung

Revolutionizing Digital Healthcare Through Artificial Intelligence and Automation: Principles, Technologies, and Applications is a transformative exploration of how Artificial Intelligence (AI) and automation technologies are reshaping the healthcare landscape. In an era where precision, efficiency, and accessibility in medical services are paramount, this book delves into cutting-edge advancements in AI-powered diagnostics, wearable smart devices, and automated patient care systems. It stands as a beacon for innovators and healthcare professionals who aim to harness technology to streamline processes, improve patient outcomes, and create sustainable solutions in an ever-evolving industry. Beyond its focus on AI and automation, the book also examines the ethical implications and challenges of integrating technology into healthcare. It discusses strategies for implementing these technologies while ensuring patient privacy, maintaining human connection in care delivery, and navigating regulatory hurdles. With detailed case studies and forward-looking insights, the text provides a comprehensive roadmap for leveraging digital tools to shape the future of healthcare.

Produktdetails

• Verlag: Elsevier Science
• Seitenzahl: 668
• Erscheinungstermin: 24. Oktober 2025
• Englisch
• Gewicht: 450g
• ISBN-13: 9780443364341
• ISBN-10: 0443364346
• Artikelnr.: 73729344

Inhaltsangabe

1. Principles and models of digital healthcare ecosystem
2. The role of artificial intelligence and generative artificial
intelligence in digital healthcare
3. An extensive analysis of artificial intelligence and internet of
things for modern healthcare realm
4. Applications of artificial intelligence and gen artificial
intelligence in digital healthcare ecosystem
5. Advancements and applications in the smart healthcare ecosystem
6. Enhancing healthcare services with artificial intelligence and
generative artificial intelligence technologies
7. Integrating artificial intelligence and internet of things for smart
healthcare systems
8. Internet of things-based technologies for smart healthcare system
9. Automation and robotics in medical laboratory services
10. Sensor technologies and applications for smart healthcare system
11. 6G communication network for smart healthcare system
12. Augmented reality and virtual reality technologies for smart
healthcare system
13. Challenges in implementing quantum technology in healthcare systems
14. AI-based blockchain for smart healthcare system
15. New neural network methods for the detection of heart diseases
16. Artificial internet of things (AIoT)-assisted disease diagnosis model
for intelligent healthcare system
17. Machine learning for cardiac rehabilitation through the internet of
medical things in smart healthcare system
18. Identify and classify brain tumors using deep learning techniques and
magnetic resonance imaging
19. Data mining for fractal measurements features related to breast tumor
analysis
20. Artificial intelligence and machine learning in modern healthcare
ecosystem
21. Recent advances in the development and application of biosensors for
the detection of endocrine disruptor
22. Optimizing ML algorithms for real-time privacy-preserving patient
monitoring in embedded systems
23. Digital edge detection algorithms for accurate pneumonia detection in
chest radiographs
24. Employing AI-powered clinical decision support to revolutionize
healthcare
25. Ergonomic designs in smart pills and biosensors for optimizing user
experience
26. Medical laboratory monitoring and total quality management for a
smart medical laboratory
27. Robotics automation for smart healthcare system and medical
laboratory service
28. Big data analytics for smart healthcare system
29. Cybersecurity and privacy data associated with services of smart
healthcare
30. Transforming healthcare from telemedicine to AI: Principles, models,
future prospects, challenges, and barriers in the digital ecosystem
31. Artificial intelligence techniques for biosensor data analysis
32. Integration of AI and AR in medical imaging: A quantitative analysis
of workflow optimization and diagnostic performance
33. Machine learning for biosensor signal processing
34. Revolutionizing medical imaging and diagnostics through advanced AI
and augmented reality technologies
35. Future prospects, challenges and ethics of cutting-edge technologies
in smart healthcare system