• Kapcsolat

  • Hírlevél

  • Rólunk

  • Szállítási lehetőségek

  • Prospero könyvpiaci podcast

  • Hírek

  • The Radiology AI Handbook

    The Radiology AI Handbook by Eltorai, Adam E.M.; Hillis, James M.; Chand, Rajat;

      • 13% KEDVEZMÉNY?

      • A kedvezmény csak az 'Értesítés a kedvenc témákról' hírlevelünk címzettjeinek rendeléseire érvényes.
      • Kiadói listaár EUR 146.99
      • Az ár azért becsült, mert a rendelés pillanatában nem lehet pontosan tudni, hogy a beérkezéskor milyen lesz a forint árfolyama az adott termék eredeti devizájához képest. Ha a forint romlana, kissé többet, ha javulna, kissé kevesebbet kell majd fizetnie.

        60 964 Ft (58 061 Ft + 5% áfa)
      • Kedvezmény(ek) 13% (cc. 7 925 Ft off)
      • Kedvezményes ár 53 039 Ft (50 513 Ft + 5% áfa)

    60 964 Ft

    db

    Beszerezhetőség

    Még nem jelent meg, de rendelhető. A megjelenéstől számított néhány héten belül megérkezik.

    Why don't you give exact delivery time?

    A beszerzés időigényét az eddigi tapasztalatokra alapozva adjuk meg. Azért becsült, mert a terméket külföldről hozzuk be, így a kiadó kiszolgálásának pillanatnyi gyorsaságától is függ. A megadottnál gyorsabb és lassabb szállítás is elképzelhető, de mindent megteszünk, hogy Ön a lehető leghamarabb jusson hozzá a termékhez.

    A termék adatai:

    • Kiadó Elsevier Health Sciences
    • Megjelenés dátuma 2025. december 22.

    • ISBN 9780323877602
    • Kötéstípus Puhakötés
    • Terjedelem oldal
    • Méret 228x152 mm
    • Súly 450 g
    • Nyelv angol
    • 700

    Kategóriák

    Hosszú leírás:

    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.

    Több

    Tartalomjegyzék:

    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

    Több