Artificial Intelligence in Healthcare and COVID-19

Artificial Intelligence in Healthcare and COVID-19 provides theoretical concepts and perspectives on implementing AI in healthcare, particularly in combating COVID-19. The book covers medical and technological visions and is relevant for universities, medical schools, professors, industry practitioners, and professionals in the R&D team of medical and informatics companies.

Format: Paperback / softback
Length: 224 pages
Publication date: 24 May 2023
Publisher: Elsevier Science & Technology

Artificial Intelligence (AI) has been gaining significant attention in the healthcare industry, particularly in response to the COVID-19 pandemic. This book explores theoretical concepts, implementational and research perspectives surrounding AI, making it an invaluable resource for healthcare professionals and researchers alike.

The book addresses both medical and technological visions, making it highly applicable to the healthcare sector. In the wake of the COVID-19 pandemic, it has become evident that leading universities and medical schools must incorporate these topics and case studies into their health informatics courses to stay abreast of the rapid technological and medical advancements. This book will also be of great value to professors teaching courses in health informatics, industry practitioners, and professionals working in the Research and Development (R&D) teams of leading medical and informatics companies who are eager to embrace AI and eHealth to combat COVID-19.

However, it is worth noting that AI in healthcare is a relatively new field, particularly when applied to COVID-19. As a result, there is a scarcity of literature in this area, particularly for students and researchers who may struggle to rely on the limited published papers or whitepapers by tech giants. This book aims to fill this gap by providing a comprehensive and up-to-date overview of AI in healthcare and COVID-19.

Chapter 1: Introduction to AI in Healthcare

This chapter provides an overview of AI in healthcare, including its historical development, current applications, and potential future directions. It discusses the various AI technologies and techniques used in healthcare, such as machine learning, natural language processing, and computer vision. The chapter also highlights the ethical and regulatory considerations associated with AI in healthcare.

Chapter 2: Theoretical Concepts and Frameworks

In this chapter, the authors explore the theoretical concepts and frameworks that underpin AI in healthcare. They discuss the principles of machine learning, natural language processing, and computer vision, and how these technologies can be applied to healthcare. The chapter also explores the challenges and limitations of AI in healthcare, such as data privacy, bias, and interpretability.

Chapter 3: Implementational Perspectives

This chapter focuses on the practical aspects of implementing AI in healthcare. It discusses the challenges and opportunities associated with integrating AI into healthcare systems, such as data acquisition, processing, storage, and analysis. The chapter also explores the role of healthcare professionals in developing and deploying AI-based solutions.

Chapter 4: Research Perspectives

This chapter explores the research perspectives surrounding AI in healthcare. It discusses the current research trends in AI, such as deep learning, natural language processing, and computer vision, and how these trends can be applied to healthcare. The chapter also highlights the importance of interdisciplinary research in developing effective AI-based solutions.

Chapter 5: Case Studies

In this chapter, the authors present case studies of AI in healthcare and COVID-19. These case studies showcase the practical applications of AI in healthcare, including disease diagnosis, treatment planning, and patient monitoring. The chapter also discusses the challenges and limitations of AI in these applications.

Chapter 6: Conclusion

In this chapter, the authors summarize the key findings and recommendations of the book. They discuss the future of AI in healthcare and COVID-19, and the role that healthcare professionals, researchers, and policymakers can play in driving the development and adoption of AI-based solutions.

In conclusion, Artificial Intelligence in Healthcare and COVID-19 is a comprehensive and timely book that provides a valuable resource for healthcare professionals, researchers, and policymakers. The book explores theoretical concepts, implementational perspectives, research perspectives, and case studies surrounding AI in healthcare and COVID-19. By providing a comprehensive overview of these topics, the book aims to help readers better understand the potential benefits and challenges of AI in healthcare and COVID-19, and how they can be leveraged to improve patient outcomes and enhance the efficiency of healthcare systems.

Weight: 464g
Dimension: 188 x 229 x 15 (mm)
ISBN-13: 9780323905312