New publication: "Trustworthy AI in medical imaging" by Marco Lorenzi and Maria A. Zuluaga
Knowledge transfer - Industry
Innovation
Research
Health
Published on December 13, 2024–Updated on December 17, 2024
Dates
on the December 30, 2024
The book "Trustworthy AI in Medical Imaging" by Marco Lorenzi and Maria A. Zuluaga and prefaced by Nicholas Ayache and Jim Duncan, is now available.
We are very pleased to announce the publication of the book “Trustworthy AI in Medical Imaging”, written by Marco Lorenzi and Maria A. Zuluaga, both 3IA Chairholders, with a foreword by Nicholas Ayache, Scientific Director and 3IA Chairholder, and Jim Duncan (Yale University).
This comprehensive guide to reliable artificial intelligence in medical imaging serves as a crucial bridge between theoretical AI research and real-world healthcare applications. By uniting the expertise of scientific researchers, medical professionals, and industry specialists, the book offers invaluable insights into building trustworthy AI systems for medical imaging.
Whether you are an undergraduate student, pursuing a master's degree, or conducting research in AI-powered medical imaging, this resource provides essential knowledge about implementing dependable AI solutions. Readers will gain a solid foundation in AI reliability principles while learning how to apply them specifically to medical imaging challenges. The book delves into common obstacles and their solutions, examines the current state of trustworthy AI in medical imaging including its limitations, and explores emerging opportunities for innovation in this rapidly evolving field.
Through this carefully curated exploration of AI trustworthiness in healthcare imaging, readers will develop the skills needed to evaluate, enhance, and advance the reliability of AI systems in medical applications.
"Trustworthy AI in Medical Imaging"
Edited by Marco Lorenzi
EPIONE team of Inria Sophia Antipolis and
Université Côte d’Azur Maria A. Zuluaga
Data Science Department
EURECOM Available on Elsevier online shop
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