Deep Learning in Biomedical and Health Informatics: Current Applications and Possibilities

This book explores the relationship between Artificial Intelligence (AI) and healthcare, discussing how AI is transforming the industry and the role of deep learning in diagnosis and disease prediction. It provides a comprehensive review of research applying deep learning in health informatics across medical imaging, electronic health records, genomics, and sensing, highlighting challenges and applications. The editors aim to provide new theories, techniques, and developments in deep learning for solving emerging problems in healthcare and other domains.

Format: Paperback / softback
Length: 202 pages
Publication date: 25 September 2023
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the intricate relationship between Artificial Intelligence (AI) and healthcare, exploring how AI is revolutionizing every aspect of the healthcare industry. It also provides a detailed examination of how deep learning is poised to transform the field of diagnosis and disease prediction. The editors have assembled a comprehensive review of research applying deep learning in health informatics, encompassing areas such as medical imaging, electronic health records, genomics, and sensing. They highlight various challenges and opportunities associated with deploying deep learning in healthcare. Additionally, the book showcases real-world applications and case studies across various domains of AI in healthcare data. The editors aim to foster new theories, techniques, and developments in deep learning, while also addressing emerging problems in healthcare and other fields. This book is a valuable resource for computer scientists, biomedical engineers, and healthcare professionals engaged in research and development of deep learning techniques.

The book begins by providing an overview of the relationship between AI and healthcare, highlighting the transformative potential of AI in improving patient outcomes and enhancing healthcare efficiency. It then delves into the applications of deep learning in diagnosis and disease prediction. The editors present a comprehensive review of research applying deep learning in health informatics across multiple fields, including medical imaging, electronic health records, genomics, and sensing. They discuss the challenges and opportunities associated with deploying deep learning in healthcare, such as data privacy, bias, and interpretability.

One of the key strengths of the book is its comprehensive coverage of research applying deep learning in health informatics. The editors have assembled a diverse collection of research papers from leading institutions around the world, providing a thorough understanding of the latest developments in the field. The review includes a wide range of topics, from image recognition and segmentation to natural language processing and machine learning algorithms. The authors of these research papers offer insights into their methodologies, results, and implications for healthcare practice.

Another notable feature of the book is its emphasis on the practical applications of deep learning in healthcare. The editors have included case studies and real-world examples that demonstrate how deep learning is being used to improve patient care, diagnose diseases, and manage healthcare resources. These examples showcase the potential of deep learning to transform healthcare delivery and enhance patient outcomes.

In addition to its technical content, the book also provides valuable insights into the ethical and societal implications of deploying AI in healthcare. The editors discuss the importance of transparency, accountability, and fairness in the development and deployment of AI-based solutions. They also address the challenges of ensuring that AI is used in a responsible and ethical manner, particularly when it comes to sensitive healthcare data.

Overall, this book is a must-read for anyone interested in the intersection of AI and healthcare. It provides a comprehensive and up-to-date overview of the latest research, applications, and challenges in the field. The editors have assembled a diverse team of experts from both academia and industry, ensuring that the book offers a balanced and insightful perspective on the future of AI in healthcare.

Weight: 453g
Dimension: 234 x 156 (mm)
ISBN-13: 9780367751548