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.- 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- Any additional digital ancillary content may publish up to 6 weeks following the publication date
Table of Contents
PART I Background1. AI in Radiology—Past and Present2. AI in Radiology—Future3. Technical PrinciplesPART II Interpretive Applications4. Interpretive Applications of Artificial Intelligence in Breast Radiology5. Artificial Intelligence in Cardiovascular Imaging6. Interpretive Applications: Chest7. Artificial Intelligence in Emergency Radiology8. Artificial Intelligence in Gastrointestinal Imaging9. Genitourinary10. ArtificiaI Intelligence in Head and Neck Radiology: Current Innovations, Challenges, and Future Directions11. Interpretive Applications: Musculoskeletal12. Neuroradiology13. Interpretive Applications of Artificial Intelligence in Interventional Radiology14. Artificial Intelligence in Nuclear Radiology: Unlocking the Potential for Enhanced PatientPART III Noninterpretive Applications15. Patient Facing Noninterpretive Artificial Intelligence Applications16. Navigating the Radiologic Technologist's Landscape: Current Innovations and Future Directions of Artificial Intelligence in Radiology17. Business-Facing Approaches18. Noninterpretive Application of Artificial Intelligence in Radiology:Population HealthPART IV Develop Your Application19. Data Curation20. Artificial Intelligence Network Training and Validation in Radiology: Recent Developments and Real-World Examples21. Regulatory Considerations for Radiology Artificial Intelligence/Machine Learning DevicesPART V Case Studies22. Response to COVID With Artificial Intelligence—Assisted Radiologic Diagnosis23. Arterys Artificial Intelligence: Inception, Development, Growth24. Viz.ai—Pioneering Artificial Intelligence in Healthcare
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