Image Classification
timm
English
medical-imaging
knee-mri
acl-tear-detection
deep-learning
convnext
self-attention
masked-slice-modeling
radiology
orthopedics
Eval Results (legacy)
Instructions to use shareefch1413/ACL-LKNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use shareefch1413/ACL-LKNet with timm:
import timm model = timm.create_model("hf-hub:shareefch1413/ACL-LKNet", pretrained=True) - Notebooks
- Google Colab
- Kaggle
File size: 610 Bytes
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{
"auroc": 0.9086438923395445,
"auprc": 0.7110100982131922,
"accuracy": 0.8805309734513275,
"balanced_acc": 0.7428830227743272,
"f1": 0.6197183098591549,
"mcc": 0.5649741787757137,
"sensitivity": 0.5238095238095238,
"specificity": 0.9619565217391305,
"fold": 4
},
{
"auroc": 0.8667831262939958,
"auprc": 0.6765005627552587,
"accuracy": 0.8628318584070797,
"balanced_acc": 0.7320134575569358,
"f1": 0.5866666666666667,
"mcc": 0.5111414540586645,
"sensitivity": 0.5238095238095238,
"specificity": 0.9402173913043478,
"fold": 5
}
] |