Dimensions Of Intelligent Analytics For Smart Digital Health Solutions
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Dimensions of Intelligent Analytics for Smart Digital Health Solutions
This title demystifies artificial intelligence (AI) and analytics, upskilling individuals (healthcare professionals, hospital managers, consultants, researchers, students, and the population at large) around analytics and AI as it applies to healthcare. This book shows how the tools, techniques, technologies, and tactics around analytics and AI can be best leveraged and utilised to realise a healthcare value proposition of better quality, better access and high value for everyone every day, everywhere. The book presents a triumvirate approach including technical, business and medical aspects of data and analytics and by so doing takes a responsible approach to this key area. This work serves to introduce the critical issues in AI and analytics for healthcare to students, practitioners, and researchers.
Dimensions of Intelligent Analytics for Smart Digital Health Solutions
This title demystifies artificial intelligence (AI) and analytics, upskilling individuals (healthcare professionals, hospital managers, consultants, researchers, students, and the population at large) around analytics and AI as it applies to healthcare. This book shows how the tools, techniques, technologies, and tactics around analytics and AI can be best leveraged and utilised to realise a healthcare value proposition of better quality, better access and high value for everyone every day, everywhere. The book presents a triumvirate approach including technical, business and medical aspects of data and analytics and by so doing takes a responsible approach to this key area. This work serves to introduce the critical issues in AI and analytics for healthcare to students, practitioners, and researchers.
Scalable Artificial Intelligence for Healthcare
This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.