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Elsevier

The Radiology AI Handbook

  • 1 Edición - 6 de octubre de 2025
  • Última edición
  • Editores: Adam E.M. Eltorai, James M. Hillis, Rajat Chand, Sudhen B. Desai, Katherine P. Andriole
  • Idioma: Inglés

**Selected for 2026 Doody's Core Titles in Diagnostic Radiology**Artificial intelligence has the potential to transform many areas of medicine and is already a growing factor… Leer más

Descripción

**Selected for 2026 Doody's Core Titles in Diagnostic Radiology**

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.

Puntos claves

  • 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

De interès para

Radiologists, residents, trainees, clinicians, emergency medicine physicians

Índice

PART I Background

1. AI in Radiology—Past and Present

2. AI in Radiology—Future

3. Technical Principles

PART II Interpretive Applications

4. Interpretive Applications of Artificial Intelligence in Breast Radiology

5. Artificial Intelligence in Cardiovascular Imaging

6. Interpretive Applications: Chest

7. Artificial Intelligence in Emergency Radiology

8. Artificial Intelligence in Gastrointestinal Imaging

9. Genitourinary

10. ArtificiaI Intelligence in Head and Neck Radiology: Current Innovations, Challenges, and Future Directions

11. Interpretive Applications: Musculoskeletal

12. Neuroradiology

13. Interpretive Applications of Artificial Intelligence in Interventional Radiology

14. Artificial Intelligence in Nuclear Radiology: Unlocking the Potential for Enhanced Patient

PART III Noninterpretive Applications

15. Patient Facing Noninterpretive Artificial Intelligence Applications

16. Navigating the Radiologic Technologist’s Landscape: Current Innovations and Future Directions of Artificial Intelligence in Radiology

17. Business-Facing Approaches

18. Noninterpretive Application of Artificial Intelligence in Radiology:
Population Health

PART IV Develop Your Application

19. Data Curation

20. Artificial Intelligence Network Training and Validation in Radiology: Recent Developments and Real-World Examples

21. Regulatory Considerations for Radiology Artificial Intelligence/Machine Learning Devices

PART V Case Studies

22. Response to COVID With Artificial Intelligence—Assisted Radiologic Diagnosis

23. Arterys Artificial Intelligence: Inception, Development, Growth

24. Viz.ai—Pioneering Artificial Intelligence in Healthcare

Detalles del producto

  • Edición: 1
  • Última edición
  • Publicado: 6 de octubre de 2025
  • Idioma: Inglés

Sobre los editores

AE

Adam E.M. Eltorai

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.

Afiliaciones y experiencia
Harvard Medical School, Boston, MA, USA

RC

Rajat Chand

Dr. Rajat Chand is a board-certified adult and pediatric interventional radiologist.
Afiliaciones y experiencia
Adult and Pediatric Diagnostic and Interventional Radiologist, Advanced Cardiac Life Support, Chapel Hill, NC

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