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Computational Intelligence for Patient Care: Blockchain, AI, and ML in Healthcare

Edited by Rishabha Malviya, Edited by Rishav Sharma, Edited by Sathvik Belagodu Sridhar, Edited by Suraj Kumar

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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 AIâ€™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 intelligenceâ€™s transformative potential in this field.

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