Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/58213
Title: Artificial Intelligence Applications for Imaging Metabolic Bone Diseases
Authors: Isaac, Amanda
Akdogan, Asli Irmak
Dalili, Danoob
Saber, Nuran
Drobny, David
Guglielmi, Giuseppe
Modat, Marc
Keywords: artificial intelligence
deep learning
machine learning
natural language processing
computer vision
Age Assessment
Spine
Prediction
Models
Interventions
Population
Validation
Fractures
Medicine
Impact
Publisher: Thieme Medical Publ Inc
Abstract: Artificial intelligence (AI) has significantly impacted the field of medical imaging, particularly in diagnosing and managing metabolic bone diseases (MBDs) such as osteoporosis and osteopenia, Paget's disease, osteomalacia, and rickets, as well as rare conditions such as osteitis fibrosa cystica and osteogenesis imperfecta. This article provides an in-depth analysis of AI techniques used in imaging these conditions, recent advancements, and their clinical applications. It also explores ethical considerations and future perspectives. Through comprehensive examination and case studies, we highlight the transformative potential of AI in enhancing diagnostic accuracy, improving patient outcomes, and contributing to personalized medicine. By integrating AI with existing imaging techniques, we can significantly enhance the capabilities of medical imaging in diagnosing, monitoring, and treating MBDs. We also provide a comprehensive overview of the current state, challenges, and future prospects of AI applications in this crucial area of health care.
URI: https://doi.org/10.1055/s-0044-1789218
https://hdl.handle.net/11499/58213
ISSN: 1089-7860
1098-898X
Appears in Collections:PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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