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Full Description
Computational Intelligence for Patient Care: Blockchain, AI, and ML in Healthcare explores the revolutionizing applications of blockchain, artificial intelligence, and machine learning in healthcare systems. The book attempts to close the gap between cutting-edge computational approaches and real-world healthcare applications by discussing the latest innovations in the field.
The book is divided into ten chapters, each of which focuses on a crucial area of healthcare-related computational intelligence. The book first provides an overview of blockchain technology and its uses in the healthcare industry, highlighting its potential for clinical research, medical fraud detection, and electronic health records (EHRs). It further explores the use of blockchain technology in the creation of digital healthcare systems, emphasizing the benefits of combining big data with blockchain technology while also going over institutional considerations and security issues.
The book goes on to discusses the use of AI in healthcare, covering topics such as the development of telemedicine, AI-assisted remote monitoring, and smart health monitoring systems. Additionally, the book explores AI's inclusive approach to disease management, management of chronic illnesses, accuracy of diagnoses, and personalized therapy. It also covers the development of AI and ML in CNS drug discovery, emphasizing novel uses of these technologies in the development of pharmaceuticals for neurological disorders. It also discusses the problems and duties of regulators in regulating the integration of AI in healthcare, providing insights into future regulatory policies.
The book will be an invaluable resource for those looking to use technology to improve patient care and healthcare outcomes, showing computational intelligence's transformative potential in this field.
Contents
Preface Foreword by Dr. Dhruv Galgotia 1. Blockchain: A Distributed Ledger Technology for Patient Care 2. Development of Digital Healthcare with Blockchain: Prospects for Patient Care 3. Improvement of Patient Outcomes with Artificial Intelligence 4. Telemonitoring: Artificial Intelligence to Monitor Patients Remotely 5. Disease Management and Patient Care with Artificial Intelligence 6. Intelligent Blockchain-Based Healthcare Data Management Systems for Patient Care 7. Transforming Cardiovascular Health: AI-Driven Diagnostic and Therapeutic Strategies 8. Revolutionizing Ophthalmology with AI and Deep Learning 9. Advancement of AI and ML in Drug Discovery for the Central Nervous System Diseases 10. Navigating the Regulatory Landscape: Addressing Challenges in AI Integration within Healthcare Index
