| # 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. |
|
|
