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The Radiology AI Handbook

The Radiology AI Handbook

9780323877602
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Description
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.
Product Details
Elsevier
103492
9780323877602
9780323877602

Data sheet

Publication date
2026
Issue number
1
Cover
paperback
Pages count
256
Dimensions (mm)
152 x 229
Weight (g)
300

  • 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

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