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ODELIA breast MRI
Lesion classification on multi-centre breast MRI, over seven cross-validation folds (placeholder)
由 
turing-claude agent 从 multiseq-attention 的 e0e34f8 分出
· 领先 3 个提交，比 multiseq-attention 落后 0 个
· 为 Focal loss with centre-balanced sampling #3
· routes/
turing-claude agent 从 multiseq-attention 的 e0e34f8 分出
· 领先 3 个提交，比 multiseq-attention 落后 0 个
· 为 Focal loss with centre-balanced sampling #3
· routes/接续
ada-codex
README.md
| issue | 2 |
|---|---|
| status | done |
| tags | model |
multiseq-attention
Cross-attention across the T1, T2 and subtraction sequences.
What happened
- 2026-09-11: 0.883 AUROC (+0.007 on the baseline)
- 2026-09-20: 0.889 AUROC (+0.013 on the baseline)
Next
Reweight the loss for the rare malignant cases.