AI for Radiology by Marques, Oge;

Sorozatcím: AI for Everything;

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A termék adatai:

Kiadás sorszáma 1
Kiadó CRC Press
Megjelenés dátuma 2024. február 12.

ISBN 9780367627256
Kötéstípus Puhakötés
Terjedelem236 oldal
Méret 198x129 mm
Súly 263 g
Nyelv angol
Illusztrációk 4 Illustrations, black & white; 2 Illustrations, color; 4 Line drawings, black & white; 2 Line drawings, color; 1 Tables, black & white

Kategóriák

Rövid leírás:

Artificial Intelligence has revolutionised areas of medicine. This book focuses on the integral role of AI in radiology, shedding light on how this technology can enhance patient care and streamline professional workflows.

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Hosszú leírás:

Artificial intelligence (AI) has revolutionized many areas of medicine and is increasingly being embraced. This book focuses on the integral role of AI in radiology, shedding light on how this technology can enhance patient care and streamline professional workflows.

This book reviews, explains, and contextualizes some of the most current, practical, and relevant developments in artificial intelligence and deep learning in radiology and medical image analysis. AI for Radiology presents a balanced viewpoint of the impact of AI in these fields, underscoring that AI technologies are not intended to replace radiologists but rather to augment their capabilities, freeing professionals to focus on more complex cases. This book guides readers from the basic principles of AI to their practical applications in radiology, moving from the role of data in AI to the ethical and regulatory considerations of using AI in radiology and concluding with a selection of resources for further exploration.

This book has been crafted with a diverse readership in mind. It is a valuable asset for medical professionals eager to stay up to date with AI developments, computer scientists curious about AI’s clinical applications, and anyone interested in the intersection of healthcare and technology.

“The book is not just about the present state of affairs. It offers a vision, exploring the future trajectories of AI in radiology, addressing challenges, controversies, and the endless possibilities on the horizon.

Having witnessed Oge’s dedication and forward-thinking approach firsthand, I am confident that this book will serve as an invaluable resource. For those stepping into the realm of AI in radiology or seeking to deepen their knowledge, this book provides a holistic, scientifically rigorous, and practical guide…I wholeheartedly believe that it will stand as a cornerstone for all enthusiasts eager to delve into the world of AI in Radiology.”

--Felipe Kitamura, MD, PhD

Director of Applied Innovation and AI at Dasa

Affiliated Professor of Radiology at Universidade Federal de São Paulo

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