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Revolutionizing Digital Healthcare Through Artificial Intelligence and Automation

Principles, Technologies, and Applications

AvAlex Khang

Häftad, Engelska, 2025

1 779 kr

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Beskrivning

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.

Covers the cutting-edge medical technologies being used and developed for the smart digital healthcare ecosystem
Provides scenarios for learning to remotely monitor, manage, and control devices
Presents insights on how to glean actionable information from massive streams of real-time data in the smart digital healthcare ecosystem
Discusses both the medical technologies involved in a smart digital Healthcare sector and the security issues that need to be integral in the digital healthcare ecosystem

Produktinformation

Utgivningsdatum:2025-10-24
Mått:230 x 20 x 190 mm
Vikt:1 385 g
Format:Häftad
Språk:Engelska
Antal sidor:668
Förlag:Elsevier Science
ISBN:9780443364341

Utforska kategorier

Biologi inom Naturvetenskap och teknik
Hälso- och sjukvård inom Medicin
Artificiell intelligens inom Data och IT

Mer om författaren

Alex Khang is an AI and Data scientist, and Chief of technology officer at the AI and Data Science Research Centre, Global Research Institute of Technology and Engineering, North Carolina, United States. Professor in Information Technology at University of Science and Technology in Vietnam, India, and United States; IT Workforce Development Consultant, Software industry expert, Software product manager and CTO for High-tech Corporations in Vietnam, EU and the United States.

Innehållsförteckning

1. Principles and models of digital healthcare ecosystem2. The role of artificial intelligence and generative artificial intelligence in digital healthcare3. An extensive analysis of artificial intelligence and internet of things for modern healthcare realm4. Applications of artificial intelligence and gen artificial intelligence in digital healthcare ecosystem5. Advancements and applications in the smart healthcare ecosystem6. Enhancing healthcare services with artificial intelligence and generative artificial intelligence technologies7. Integrating artificial intelligence and internet of things for smart healthcare systems8. Internet of things-based technologies for smart healthcare system9. Automation and robotics in medical laboratory services10. Sensor technologies and applications for smart healthcare system11. 6G communication network for smart healthcare system12. Augmented reality and virtual reality technologies for smart healthcare system13. Challenges in implementing quantum technology in healthcare systems14. AI-based blockchain for smart healthcare system15. New neural network methods for the detection of heart diseases16. Artificial internet of things (AIoT)-assisted disease diagnosis model for intelligent healthcare system17. Machine learning for cardiac rehabilitation through the internet of medical things in smart healthcare system18. Identify and classify brain tumors using deep learning techniques and magnetic resonance imaging19. Data mining for fractal measurements features related to breast tumor analysis20. Artificial intelligence and machine learning in modern healthcare ecosystem21. Recent advances in the development and application of biosensors for the detection of endocrine disruptor22. Optimizing ML algorithms for real-time privacy-preserving patient monitoring in embedded systems23. Digital edge detection algorithms for accurate pneumonia detection in chest radiographs24. Employing AI-powered clinical decision support to revolutionize healthcare25. Ergonomic designs in smart pills and biosensors for optimizing user experience26. Medical laboratory monitoring and total quality management for a smart medical laboratory27. Robotics automation for smart healthcare system and medical laboratory service28. Big data analytics for smart healthcare system29. Cybersecurity and privacy data associated with services of smart healthcare30. Transforming healthcare from telemedicine to AI: Principles, models, future prospects, challenges, and barriers in the digital ecosystem31. Artificial intelligence techniques for biosensor data analysis32. Integration of AI and AR in medical imaging: A quantitative analysis of workflow optimization and diagnostic performance33. Machine learning for biosensor signal processing34. Revolutionizing medical imaging and diagnostics through advanced AI and augmented reality technologies35. Future prospects, challenges and ethics of cutting-edge technologies in smart healthcare system