trifuse-ad-oasis1 / README.md
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metadata
license: other
tags:
  - alzheimer
  - oasis-1
  - structural-mri
  - multimodal
  - dementia-staging
pretty_name: TriFuse-AD OASIS-1 Three-Stage Dementia Staging

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.