fm_app skillA
fm_app is agent-read markdown (skill) from cuhk-aim-group/neurodiscovery: Use this model doc whenever the user wants to run FM-APP for phenotype prediction using fMRI ROI features and optional sMRI features. This document provides model-level usage and delegates preprocessing to fmri-skill and smri-skill..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# FM-APP Model Doc ## Overview FM-APP is a multi-stage framework for phenotype prediction via fMRI to sMRI knowledge transfer. - Paper: He Z, Li W, Liu Y, et al. FM-APP, IEEE TMI, 2024, 44(10): 4010-4022 - Official code: https://github.com/ZhibinHe/FM-APP - Primary input: fMRI ROI connectivity features - Additional input: sMRI ROI structural features (required in Stage 2) - Primary output: multi-phenotype prediction and zero-shot phenotype reconstruction In NeuroClaw, this is model-level guidance. Upstream preparation should be delegated to: - `fmri-skill` for fMRI preprocessing and ROI extraction - `smri-skill` for structural ROI feature extraction - `hcpya-skill` if HCP Young Adult download/orchestration is needed **Research use only.** --- ## Quick Start (From git clone) ### 1) Clone repository ```bash git clone https://github.com/ZhibinHe/FM-APP.git cd FM-APP ``` ### 2) Create environment and install dependencies ```bash python -m venv .venv source .venv/bin/activate pip install -r requirements.txt ``` If using GPU, install CUDA-compatible PyTorch and graph-related packages first. ### 3) Prepare required data Before training, ensure these are ready: …
Read the whole file at its exact version.
How to install
mdr add cuhk-aim-group/neurodiscovery/fm_app@git:20260506.f8d0216mdr add cuhk-aim-group/neurodiscovery/fm_app@sha256:13ac44f27f81e92fPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_p65kg65bdb5pscoc)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260506.f8d0216 latest | 2026-05-06 | f8d0216 | 5,873 B | A | view · diff |
| git:20260505.e9ddd22 | 2026-05-05 | e9ddd22 | 5,785 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5873 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
cuhk-aim-group/neurodiscovery · 91 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_p65kg65bdb5pscoc GET https://markdownregistry.com/api/v1/resolve?ref=cuhk-aim-group/neurodiscovery/fm_app GET https://markdownregistry.com/api/v1/blob/13ac44f27f81e92fd49724dd5a8f562f7cbdb3d39c0424ab35b147d6d5c04a75
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