Home / cuhk-aim-group / neurodiscovery · skills/brain-age-modeling/SKILL.md · GitHub

brain-age-modeling skillA

brain-age-modeling is agent-read markdown (skill) from cuhk-aim-group/neurodiscovery: Use this skill whenever the user wants brain-age prediction, predicted-age bias correction, Brain-PAD/brain-age gap export, cross-validated age modeling, or downstream group analysis of accelerated or delayed brain aging. Triggers include 'brain age', 'Brain-PAD', 'brain age gap', 'predicted age', 'age bias correction', 'accelerated aging', and 'neuroimaging age model'..

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What the file says

# Brain-Age Modeling Workflow

## Overview

`brain-age-modeling` is a leakage-safe task workflow over NeuroClaw regression
estimators. It trains predicted-age models, fits age-bias correction on each
training fold, and exports held-out raw age, corrected age, and Brain-PAD.

```text
Brain-PAD = bias-corrected predicted age - chronological age
```

Positive Brain-PAD indicates an older-appearing brain relative to chronological
age under the fitted model; it is not by itself a diagnosis or causal effect.

---

## Installation

```bash
pip install numpy pandas scipy scikit-learn joblib
```

Optional feature generators such as FreeSurfer, NeuroSTORM, or a 3D CNN are
handled by their own skills before this tabular brain-age workflow.

---

## Workflows

### 1. Prepare brain features

```text
subject_id,site,age,cortical_thickness,hippocampal_volume,fc_001
sub-001,A,64,2.51,3810,0.12
sub-002,B,59,2.63,4022,0.08
```

Use a healthy training reference when the scientific interpretation requires
deviation from normative aging. Do not include downstream disease outcomes as
predictors.

### 2. Ridge brain-age model

```bash
python skills/brain-age-modeling/scripts/train_reference.py \
…

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Source

GitHub

cuhk-aim-group/neurodiscovery · 91 stars · license MIT · pushed 2026-09-22 · branch main

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