Abstract
Following publication of the original article [1], we have been notified that body text contained incorrectly published parts. The original text was as follows: The accuracy was the lowest for KL grade 1 (46%) and the highest for KL grade 4 (93%). Table 2 Sensitivity and specificity of the proposed model for each Kellgren–Lawrence grade This has been corrected to: The accuracy was the lowest for KL grade 1 (43%) and the highest for KL grade 4 (96%). Sensitivity and specificity of the proposed model for each Kellgren–Lawrence grade The original article was updated.
| Original language | English |
|---|---|
| Article number | 17 |
| Journal | Knee Surgery and Related Research |
| Volume | 37 |
| Issue number | 1 |
| DOIs |
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| State | Published - Dec 2025 |
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Dive into the research topics of 'Correction to: Accurate, automated classification of radiographic knee osteoarthritis severity using a novel method of deep learning: Plug-in modules (Knee Surgery & Related Research, (2024), 36, 1, (24), 10.1186/s43019-024-00228-3)'. Together they form a unique fingerprint.Cite this
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