Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/58213
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dc.contributor.authorIsaac, Amanda-
dc.contributor.authorAkdogan, Asli Irmak-
dc.contributor.authorDalili, Danoob-
dc.contributor.authorSaber, Nuran-
dc.contributor.authorDrobny, David-
dc.contributor.authorGuglielmi, Giuseppe-
dc.contributor.authorModat, Marc-
dc.date.accessioned2024-11-20T18:03:31Z-
dc.date.available2024-11-20T18:03:31Z-
dc.date.issued2024-
dc.identifier.issn1089-7860-
dc.identifier.issn1098-898X-
dc.identifier.urihttps://doi.org/10.1055/s-0044-1789218-
dc.identifier.urihttps://hdl.handle.net/11499/58213-
dc.description.abstractArtificial 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.en_US
dc.language.isoenen_US
dc.publisherThieme Medical Publ Incen_US
dc.relation.ispartofSeminars in Musculoskeletal Radiologyen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial intelligenceen_US
dc.subjectdeep learningen_US
dc.subjectmachine learningen_US
dc.subjectnatural language processingen_US
dc.subjectcomputer visionen_US
dc.subjectAge Assessmenten_US
dc.subjectSpineen_US
dc.subjectPredictionen_US
dc.subjectModelsen_US
dc.subjectInterventionsen_US
dc.subjectPopulationen_US
dc.subjectValidationen_US
dc.subjectFracturesen_US
dc.subjectMedicineen_US
dc.subjectImpacten_US
dc.titleArtificial Intelligence Applications for Imaging Metabolic Bone Diseasesen_US
dc.typeArticleen_US
dc.identifier.volume28en_US
dc.identifier.issue5en_US
dc.identifier.startpage610en_US
dc.identifier.endpage619en_US
dc.departmentPamukkale Universityen_US
dc.authoridIsaac, Amanda/0000-0001-5827-0562-
dc.identifier.doi10.1055/s-0044-1789218-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid57192649326-
dc.authorscopusid57211281448-
dc.authorscopusid57203802559-
dc.authorscopusid59369447800-
dc.authorscopusid57204489643-
dc.authorscopusid7005143760-
dc.authorscopusid24376919100-
dc.authorwosidIsaac, Amanda/AAF-2563-2020-
dc.identifier.pmid39406223en_US
dc.identifier.scopus2-s2.0-85206551043en_US
dc.identifier.wosWOS:001339263400005en_US
dc.institutionauthor-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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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