Artificial Intelligence for Innovative Healthcare Informatics

This book discusses the challenges in Biomedical Imaging and how to solve them using computational analytics. It brings together technologies such as Image Processing, Machine Learning, and Computer Aided Systems to apply them to Biomedical Imaging.

Format: Hardback
Length: 327 pages
Publication date: 24 May 2022
Publisher: Springer Nature Switzerland AG

Numerous renowned publications in the field of Healthcare Computational Informatics have emerged, offering valuable insights into the realm of computational bioengineering and bioinformatics. These include Computational Bioengineering and Bioinformatics (2020), published by Springer; Health Informatics (2017), also published by Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), released by IOS Press; and Data Analytics in Biomedical Engineering and Healthcare (2020), published by Elsevier. While these books provide comprehensive coverage of various aspects of healthcare informatics, they tend to address the challenges of biomedical imaging in a one-dimensional manner, relying solely on specific technologies such as image processing, machine learning, or computer-aided systems.

In an effort to bridge this gap, this book presents a comprehensive approach that brings together a diverse range of computational analytics technologies and applies them to biomedical imaging. By integrating these technologies, the book aims to provide a holistic framework for addressing the complex challenges associated with biomedical imaging, enabling researchers and practitioners to extract valuable insights and make informed decisions.

The book begins by introducing the fundamental principles of biomedical imaging and the various imaging modalities used in healthcare. It then delves into the realm of computational analytics, exploring techniques such as artificial intelligence, machine learning, and big data analytics. These technologies are applied to biomedical imaging to address specific challenges, such as image segmentation, object detection, and medical image analysis.

Furthermore, the book discusses the importance of integrating computational analytics with medical expertise and ethical considerations. It highlights the need for interdisciplinary collaboration and the development of robust algorithms that can handle large datasets and complex imaging modalities.

The book concludes by providing case studies and examples that illustrate the practical applications of computational analytics in biomedical imaging. These examples showcase the potential of these technologies to improve patient care, enhance medical research, and accelerate drug discovery.

In summary, this book offers a comprehensive and interdisciplinary approach to biomedical imaging, leveraging the power of computational analytics to address the complex challenges associated with this field. By integrating a diverse range of technologies and promoting interdisciplinary collaboration, the book aims to advance the field of healthcare informatics and contribute to improved patient outcomes.

Weight: 670g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030965686
Edition number: 1st ed. 2022