Article ; Online: OMERACT validation of a deep learning algorithm for automated absolute quantification of knee joint effusion versus manual semi-quantitative assessment.
Seminars in arthritis and rheumatism
2024 Volume 66, Page(s) 152420
Abstract: Objective: To begin evaluating deep learning (DL)-automated quantification of knee joint effusion-synovitis via the OMERACT filter.: Methods: A DL algorithm previously trained on Osteoarthritis Initiative (OAI) knee MRI automatically quantified ... ...
Abstract | Objective: To begin evaluating deep learning (DL)-automated quantification of knee joint effusion-synovitis via the OMERACT filter. Methods: A DL algorithm previously trained on Osteoarthritis Initiative (OAI) knee MRI automatically quantified effusion volume in MRI of 53 OAI subjects, which were also scored semi-quantitatively via KIMRISS and MOAKS by 2-6 readers. Results: DL-measured knee effusion correlated significantly with experts' assessments (Kendall's tau 0.34-0.43) CONCLUSION: The close correlation of automated DL knee joint effusion quantification to KIMRISS manual semi-quantitative scoring demonstrated its criterion validity. Further assessments of discrimination and truth vs. clinical outcomes are still needed to fully satisfy OMERACT filter requirements. |
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Language | English |
Publishing date | 2024-02-17 |
Publishing country | United States |
Document type | Journal Article |
ZDB-ID | 120247-9 |
ISSN | 1532-866X ; 0049-0172 |
ISSN (online) | 1532-866X |
ISSN | 0049-0172 |
DOI | 10.1016/j.semarthrit.2024.152420 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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