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survival-models SKILL.md skillA

survival-models from cuhk-aim-group/neurodiscovery is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned

mdr add cuhk-aim-group/neurodiscovery/survival-models@git:20260825.cbd02ff

Pins git:20260825.cbd02ff in mdr.lock. Pin the fingerprint instead.

Audit grade: A, 17 of 17 checks passed
Kind: SKILL.md skill
Repository: cuhk-aim-group/neurodiscovery
Path: skills/survival-models/SKILL.md
Versions recorded: 1
Latest version: git:20260825.cbd02ff, committed Aug 25, 2026
Size: 4,004 bytes
Repository stars: 93
License: MIT

Use this skill whenever the outcome is right-censored time-to-event data, including progression, conversion, relapse, hospitalization, or mortality prediction. It supports Cox proportional hazards, Random Survival Forest, DeepSurv, and XGBoost Cox survival with censor-aware cross-validation. Triggers include 'survival analysis', 'time to event', 'censored outcome', 'Cox model', 'hazard ratio', 'Random Survival Forest', 'DeepSurv', 'XGBoost survival', 'progression', and 'conversion risk'.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Survival Models Skill

## Overview

`survival-models` trains censor-aware prognosis models from subject-level
features. Every sample requires a follow-up duration and an event indicator;
censored observations must not be converted into ordinary regression labels.

**Supported models**

| Model | Implementation | Dependency |
|---|---|---|
| `cox` | proportional hazards baseline | core |
| `rsf` | Random Survival Forest | `scikit-survival` |
| `deepsurv` | neural Cox risk model | PyTorch |
| `xgboost_survival` | XGBoost `survival:cox` | `xgboost` |

The primary metric is Harrell's concordance index. The exported prediction is
a relative risk score, not an absolute probability unless separately
calibrated at a specified time horizon.

---

## Installation

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

Optional estimators:

```bash
pip install scikit-survival
pip install xgboost
```

---

## Workflows

### 1. Prepare survival data

```text
subject_id,site,followup_days,progressed,roi_001,roi_002,age
sub-001,A,730,1,0.12,-0.04,64
sub-002,B,910,0,0.08,-0.09,59
```

`event-col` must be binary (`1` observed event, `0` censored). Duration must be
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint

mdr add cuhk-aim-group/neurodiscovery/survival-models@sha256:182953188892e6da

The line at the top of this page pins the label git:20260825.cbd02ff, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

[![mdr](https://markdownregistry.com/badge/art_2wpui2unqcpyo37o.svg)](https://markdownregistry.com/a/art_2wpui2unqcpyo37o)

5 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Aug 25, 2026.

version	committed	commit	size	audit
git:20260825.cbd02ff latest	2026-08-25	cbd02ff	4,004 B	A	view

Audit of the latest version

A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.

pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (4004 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

GitHub

cuhk-aim-group/neurodiscovery · 93 stars · license MIT · pushed 2026-10-23 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_2wpui2unqcpyo37o
GET https://markdownregistry.com/api/v1/resolve?ref=cuhk-aim-group/neurodiscovery/survival-models
GET https://markdownregistry.com/api/v1/blob/182953188892e6da429f9993407256568fb16b7929de73eec9598cad595394a1

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.