Artificial Intelligence in Cardiothoracic Imaging

Image of the book cover for 'Artificial Intelligence in Cardiothoracic Imaging'
Author: Carlo De Cecco, Marly van Assen, Tim Leiner
Affiliation: Carlo N. De Cecco, Emory University, Atlanta, GA, USA; Marly van Assen, Emory University, Atlanta, GA, USA; Tim Leiner, Mayo Clinic, Rochester, MN, USA
Publisher: Springer Nature
Publication Date: 2022
ISBN 10: 3030920860
ISBN 13: 9783030920869
eISBN: 9783030920876
Edition: 1st
This book provides an overview of current and potential applications of artificial intelligence (AI) for cardiothoracic imaging. Most AI systems used in medical imaging are data-driven and based on supervised machine learning. Clinicians and AI specialists can contribute to the development of an AI system in different ways, focusing on their respective strengths. Unfortunately, communication between these two sides is far from fluent and, from time to time, they speak completely different languages. Mutual understanding and collaboration are imperative because the medical system is based on physicians’ ability to take well-informed decisions and convey their reasoning to colleagues and patients. This book offers unique insights and informative chapters on the use of AI for cardiothoracic imaging from both the technical and clinical perspective. It is also a single comprehensive source that provides a complete overview of the entire process of the development and use of AI in clinical practice for cardiothoracic imaging. The book contains chapters focused on cardiac and thoracic applications as well more general topics on the potentials and pitfalls of AI in medical imaging. Separate chapters will discuss the valorization, regulations surrounding AI, cost-effectiveness, and future perspective for different countries and continents. This book is an ideal guide for clinicians (radiologists, cardiologists etc.) interested in working with AI, whether in a research setting developing new AI applications or in a clinical setting using AI algorithms in clinical practice. The book also provides clinical insights and overviews for AI specialists who want to develop clinically relevant AI applications.
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