Big Data And Artificial Intelligence In Ophthalmology Clinical Application And Future Exploration

Big data and artificial intelligence in ophthalmology - clinical application and future exploration

Artificial Intelligence in Healthcare

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

AI Adoption in Healthcare Industry 4.0

This book focuses on the prominent innovative business models and employability implications of artificial intelligence in the healthcare industry 4.0. To do so, it draws upon a rich base of case studies from robotics, virtual assistants, precision medicine, etc., to highlight the possibilities and implications of AI on health care. The book is useful in a variety of ways to the different stakeholders of healthcare sector. It helps medical professionals to understand the impact of the present technologies being adopted and the potential of AI-based technology. The content is of use for the policy makers as it also highlights the managerial and research implications, challenges, opportunities posed by the adoption of AI in healthcare industry 4.0. The rich case study analysis in the area of adoption of AI in healthcare helps generate insights for the academicians and researchers of this field in terms of the parallels drawn between adoptions of AI in healthcare industry 4.0 across the world. It is also useful for management students to understand the key management perspective when healthcare organizations attempt to devise strategies/policies for adoption of AI-driven technologies and processes implementation.