Image Feature Extraction
timm
Safetensors
pathology
histopathology
her2
breast-cancer
h-and-e
vision-transformer
multiple-instance-learning
Instructions to use cloudkites/her2-reader with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use cloudkites/her2-reader with timm:
import timm model = timm.create_model("hf-hub:cloudkites/her2-reader", pretrained=True) - Notebooks
- Google Colab
- Kaggle
File size: 1,853 Bytes
3c76023 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | # Data
## predictions/
One folder per reader, then per training direction and seed:
- `deployed-protocol_clam-sb_recipe-A/` — the deployed reader's protocol: CLAM-SB on 400 tiles at 0.5 um/px, our
deployed encoder. `t2y`: trained on TCGA-BRCA (490 slides), external test Yale-HER2 (192). `y2t`: trained on
Yale-HER2, external test TCGA-BRCA. Seeds 1-10; the deployed reader is `t2y/seed4`.
- `r11o_published-protocol/` — the published reader's protocol with our deployed encoder: attention MIL with non-gated
attention on every tissue tile at 1.0 um/px, trained on TCGA-BRCA (917) + CPTAC-BRCA (382), external test Yale-HER2.
Seeds 1-8 (40 models).
- `r12a_published-protocol/`, `r12b_published-protocol/` — the same protocol with the R12 encoders.
Files in each seed folder:
- `predictions.csv` — training cohort, 5-fold cross-validation: `fold, split (train/val/test), slide_id, case_id,
label, score`. Rows with `split == test` are the out-of-fold predictions.
- `external_predictions.csv` — every fold model's score on every external slide: `fold, split (external), slide_id,
case_id, label, score`. The seed's reader is the mean over its five folds.
- `results.csv` — per-fold, pooled and external-ensemble metrics (AUC with DeLong and bootstrap intervals, threshold,
sensitivity, specificity, PPV, NPV).
- `folds.csv` — which fold each slide's case was dealt into (case-stratified, fold seed 1337).
`label` is HER2 status (1 positive, 0 negative): for TCGA-BRCA from GDC clinical data, for CPTAC-BRCA from its
proteogenomic ERBB2 status, for Yale-HER2 from the collection's case labels. `score` is the probability of HER2-positive.
## paper/
`paper-data/` holds the data files our paper's build reads (tables, figure data, macros); `book-data/` holds the
files it reads from our technical report's data folder.
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