The dataset viewer is not available because its heuristics could not detect any supported data files. You can try uploading some data files, or configuring the data files location manually.
TriFuse-AD: Honest Multimodal Benchmark for Three-Stage Dementia Staging on OASIS-1
Code, processed data, results, and paper for a leakage-free benchmark of three-stage cognitive classification (CN / VMD / AD) on the OASIS-1 cross-sectional cohort, plus the proposed TriFuse-AD model (tri-planar CNN + slice-plane Transformer + gated demographic fusion).
Key result (honest / negative)
On an age-restricted cohort (≥60, 198 subjects) with subject-level repeated 5-fold CV (3 seeds, 15 runs/model), no MRI-only network beats a plain tabular XGBoost (Macro-F1 0.474), and TriFuse-AD (0.488 ± 0.066) does not significantly beat a trivial DenseNet late-concat baseline (0.497 ± 0.062; paired permutation p = 0.55). A no-MRI structured model reaches Macro-F1 0.480 — most recoverable signal is morphometric/demographic, not learned from raw voxels. No clinical / diagnostic / SOTA / MCI / cross-site claims.
Repository layout
| Path | Contents |
|---|---|
src/ |
trifuse package: data, models, training, eval, analysis |
scripts/ |
experiment runner, table/figure/interpretability builders |
configs/ |
model configs |
results/ |
per-model OOF preds, summaries, tables, 27 figures |
paper/trifuse_ad.md |
full paper draft |
data_processed.zip |
preprocessed 2.5D + 3D arrays + subjects_clean.csv (1.5 GB) |
data/raw/*.tar.gz |
OASIS-1 cross-sectional discs 1–12 (16 GB) |
Reproducing
pip install -r requirements # torch cu128, timm, monai, nibabel, xgboost, sklearn, ...
unzip data_processed.zip # -> data/processed_2d, processed_3d, metadata
python scripts/run_experiments.py --grid main # 11 models x 15 runs
python scripts/run_experiments.py --grid ablation # 6 variants
python scripts/make_tables.py && python scripts/make_figures.py
Cohort
OASIS-1, age≥60 → 198 subjects (CN=98, VMD=70, AD=30). Labels from CDR (0→CN,
0.5→VMD, ≥1→AD). CDR and MMSE are never model inputs (label leakage). One volume
per subject (*_111_t88_masked_gfc).
License / data use
The data/raw/ tarballs are the original OASIS-1 cross-sectional release
(Marcus et al., 2007), redistributed here for reproducibility. OASIS data are subject
to the OASIS data-use terms; if you use them, cite the OASIS project and comply with
their agreement. Code and derived results in this repo are provided for research use.
- Downloads last month
- 216