Overview

Artificial intelligence has the potential to transform many areas of medicine and is already a growing factor in the field of radiology. The Radiology AI Handbook offers the current, authoritative information you need in order to better understand AI and how to incorporate it into your daily practice. Written by clinical and computer science experts in AI, this book provides a comprehensive overview of the fundamental concepts, technology, research/development/validation, and regulatory considerations for current and emerging radiology AI applications in each subspecialty. Offers an indispensable introduction to this emerging field, with expert coverage of how AI can best be used in radiology. Provides clear explanations of fundamental concepts in AI and machine learning; current and future applications of AI that may affect the practice of radiology; and how to develop commercially viable AI applications in radiology. Discusses both interpretive and non-interpretive applications, and includes multiple case studies throughout. Serves as both an introduction to AI in radiology for students, trainees, and professionals, as well as a how-to guide for getting started on identifying, developing, testing, and commercializing AI applications. An eBook version is included with purchase. The eBook allows you to access all of the text, figures, and references, with the ability to search, customize your content, make notes and highlights, and have content read aloud. Additional digital ancillary content may publish up to 6 weeks following the publication date.

Full Product Details

Author:   Adam E.M. Eltorai (Harvard Medical School, Boston, MA, USA) ,  James M. Hillis ,  Rajat Chand ,  Sudhen B. Desai
Publisher:   Elsevier - Health Sciences Division
Imprint:   Elsevier - Health Sciences Division
Weight:   0.300kg
ISBN:  

9780323877602

ISBN 10:   0323877605
Pages:   256
Publication Date:   22 December 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

PART I:  BACKGROUND 1. Market overview, growth, and why 2. Fundamental concepts (e.g. AI, ML), vocabulary 3. Technology principles (e.g. modelling, learning methods, deep learning, sparse coding, big data) PART II: APPLICATIONS 1. Breast (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 2. Cardiovascular (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 3. Chest (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 4. Emergency (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 5. Gastrointestinal (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 6. Genitourinary (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 7. Head and neck (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 8. Musculoskeletal (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 9. Neuroradiology (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 10. Paediatric (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 11. Interventional (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) 12. Nuclear (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs) PART III: DEVELOP YOUR APPLICATION 13. Problem (ideation process, what problem are you solving, for whom, value prop, special sauce) 14. Team (who you need, roles) 15. R&D, validation process 16. Regulatory, quality, ethical, legal PART IV: COMMERCIALIZATION 17. Routes of commercialization 18. Funding- who, how, economics, power 19. Cases studies (stories of successful rad AI ventures)

Reviews

""This titanic encyclopedic reference continues to be the definitive leader in the dermatology world. The previous edition was published in 2018. In 2,717 pages, world experts comprehensively cover all known cutaneous diseases. Clinical presentations, etiology, treatments, and their mechanism of actions are accompanied by excellent clinical photographs, diagrams of pathophysiology, and tables summarizing genomic alterations, key features of diseases, and management tips."" (c)Doody's Review Service, 2024, Bartlomiej Bartkowiak, MD, PhD (Yale School of Medicine), Doody's Score: 91 - 4 Stars!

Author Information

Dr Adam E. M. Eltorai, MD, PhD completed his graduate studies in Biomedical Engineering and Biotechnology along with his medical degree from Brown University. His work has spanned the translational spectrum with a focus on medical technology innovation and development. Dr. Eltorai has published numerous articles and books.

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