---
license: cc0-1.0
tags: [medical-imaging, ct, intracranial-hemorrhage, rsna, conformal-prediction]
---
# ICH Phase-2 — trained models & artifacts

RSNA-2019 winner-style cascade (2D CNN -> per-slice embeddings -> BiGRU) with three novelties
(conformal risk control, cross-slice CAM-consistency, long-tail loss). Uploaded 2026-07-17.

## Contents
- `checkpoints/` — CNN + BiGRU heads (`cnn_best.pt`, `seq_winner_best.pt`, `seq_gate_best.pt`, `seq_sub_best.pt`)
- `scores/` — val/test score arrays (`*.npz`) consumed by Step 3 (conformal + manuscript)
- `embeddings/` — per-slice CNN embeddings (`emb.npy`, `emb_ids.json`) for regenerating sequence models
- `run_config.json`, `class_stats.json` — full config + data statistics

## Test-set results (macro-AUC)
- BiGRU winner reproduction: 0.933 | our cascade: 0.932 | 2D-CNN baseline: 0.856
- Epidural (rare class) AUC: 0.924