Artificial intelligence for bone disorder

• Verfasst von: Malviya, Rishabha [VerfasserIn]
• Verfasst von: Rajput, Shivam [VerfasserIn]
• Verfasst von: Vaidya, Makarand [VerfasserIn]
• Titel: Artificial intelligence for bone disorder
• Titelzusatz: diagnosis and treatment
• Verf.angabe: Rishabha Malviya, Shivam Rajput and Makarand Vaidya
• Verlagsort: Hoboken, NJ ; Beverly, MA
• Verlagsort: Hoboken, NJ ; Beverly, MA
• Verlag: Wiley
• Verlag: Scrivener Publishing
• Jahr: 2024
• Jahr: 2024
• Umfang: 1 online resource (272 pages)
• Fussnoten: Includes bibliographical references and index. - Online resource; title from PDF title page (John Wiley, viewed February 5, 2024)
• ISBN: 978-1-394-23091-4
• ISBN: 1-394-23091-5
• ISBN: 978-1-394-23088-4
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Os ; Maladies ; Informatique
• Sach-SW: Intelligence artificielle en médecine
• K10plus-PPN: 189276184X
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4544456436
• Lokale URL Inst.: Zum Volltext

Abstract

ARTIFICIAL INTELLIGENCE FOR BONE DISORDER The authors have produced an invaluable resource that connects the fields of AI and bone treatment by providing essential insights into the current state and future of AI in bone condition diagnosis and therapy, as well as a methodical examination of machine learning algorithms, deep learning approaches, and their real-world uses. The book explores the use of artificial intelligence (AI) in the diagnosis and treatment of various bone illnesses. The integration of AI approaches in the fields of orthopedics, radiography, tissue engineering, and other areas related to bone are discussed in detail. It covers tissue engineering methods for bone regeneration and investigates the use of AI tools in this area, emphasizing the value of deep learning and how to use AI in tissue engineering efficiently. The book also covers diagnostic and prognostic uses of AI in orthopedics, such as the diagnosis of disorders involving the hip and knee as well as prognoses for therapies. Chapters also look at MRI, trabecular biomechanical strength, and other methods for diagnosing osteoporosis. Other issues the book examines include several uses of AI in pediatric orthopedics, 3D modeling, digital X-ray radiogrammetry, convolutional neural networks for customized care, and digital tomography. With information on the most recent developments and potential future applications, each chapter of the book advances our understanding of how AI might be used to diagnose and treat bone problems. Audience This book will serve as a guide for orthopedic experts, biomedical engineers, faculty members, research scholars, IT specialists, healthcare workers, and hospital administrators.