Overview
- Provides a clinical and technical overview of the use of AI and big data in modern cardiovascular medicine
- Features real-world cases to assist the reader in understanding how to apply the concepts covered
- Details both the advantages and potential pitfalls in utilising artificial intelligence in cardiology
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About this book
This book provides a detailed technical overview of the use and applications of artificial intelligence (AI), machine learning and big data in cardiology. Recent technological advancements in these fields mean that there is significant gain to be had in applying these methodologies into day-to-day clinical practice. Chapters feature detailed technical reviews and highlight key current challenges and limitations, along with the available techniques to address them for each topic covered. Sample data sets are also included to provide hands-on tutorials for readers using Python-based Jupyter notebooks, and are based upon real-world examples to ensure the reader can develop their confidence in applying these techniques to solve everyday clinical problems.
Artificial Intelligence and Big Data in Cardiology systematically describes and technically reviews the latest applications of AI and big data within cardiology. It is ideal for use by the trainee and practicing cardiologist andinformatician seeking an up-to-date resource on the topic with which to aid them in develo** a thorough understanding of both basic concepts and recent advances in the field.
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Keywords
Table of contents (11 chapters)
Editors and Affiliations
About the editors
Dr. Duchateau is currently Associate Professor (Maître de Conférences) at the Université Lyon 1 and the CREATIS lab in Lyon, France, and Junior Member of the Institut Universitaire de France (IUF). His research is on the development of new statistical and machine learning approaches for the better understanding of disease apparition and evolution from medical imaging data. On the applicative side, his work has special dedication to the study of cardiac function and 2D/3D myocardial shape, motion and deformation patterns. It has a strong focus on heart failure populations, looked through echocardiographic and magnetic resonance imaging data.
Dr. King is currently a Reader in Medical Image Analysis at the School of Biomedical Engineering and Imaging Sciences at King’s College London. His research aims to develop novel machine learning methods for a range of medical applications, but with a special focus on cardiology. He works closely with clinicians to exploit the power of machine learning to solve clinically relevant problems. Notable recent successes include the prediction of treatment outcome for heart failure and automated quantification of cardiac function for patient risk stratification.Bibliographic Information
Book Title: AI and Big Data in Cardiology
Book Subtitle: A Practical Guide
Editors: Nicolas Duchateau, Andrew P. King
DOI: https://doi.org/10.1007/978-3-031-05071-8
Publisher: Springer Cham
eBook Packages: Medicine
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-05070-1Published: 05 May 2023
Softcover ISBN: 978-3-031-05073-2Published: 06 May 2024
eBook ISBN: 978-3-031-05071-8Published: 04 May 2023
Edition Number: 1
Number of Pages: IX, 216
Number of Illustrations: 1 b/w illustrations, 55 illustrations in colour
Topics: Health Informatics, Cardiology, Bioinformatics, Computer Applications