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Titel:

Artificial intelligence to analyze magnetic resonance imaging in rheumatology.

Dokumenttyp:
Review; Journal Article; Review
Autor(en):
Adams, Lisa C; Bressem, Keno K; Ziegeler, Katharina; Vahldiek, Janis L; Poddubnyy, Denis
Abstract:
Rheumatic disorders present a global health challenge, marked by inflammation and damage to joints, bones, and connective tissues. Accurate, timely diagnosis and appropriate management are crucial for favorable patient outcomes. Magnetic resonance imaging (MRI) has become indispensable in rheumatology, but interpretation remains laborious and variable. Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), offers a means to improve and advance MRI analysis. This re...     »
Zeitschriftentitel:
Joint Bone Spine
Jahr:
2024
Band / Volume:
91
Heft / Issue:
3
Volltext / DOI:
doi:10.1016/j.jbspin.2023.105651
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/37797827
Print-ISSN:
1297-319X
TUM Einrichtung:
Institut für Diagnostische und Interventionelle Radiologie (Prof. Makowski)
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