OMERACT validation of a deep learning algorithm for automated absolute quantification of knee joint effusion versus manual semi-quantitative assessment.
Semin Arthritis Rheum
; 66: 152420, 2024 Jun.
Article
en En
| MEDLINE
| ID: mdl-38422727
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.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Imagen por Resonancia Magnética
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Osteoartritis de la Rodilla
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Aprendizaje Profundo
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Articulación de la Rodilla
Límite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Semin Arthritis Rheum
Año:
2024
Tipo del documento:
Article