idc-claude-skill
🥈SilverAI skill for querying and downloading public cancer imaging data from the National Cancer Institute's Imaging Data Commons. Benefits researchers and healthcare professionals by automating data retrieval for analysis and study.
1310Updated 1w ago
Intermediate30min to implementautomation
Saves ~25 min per use
Quick InstallView Source
git clone https://github.com/ImagingDataCommons/idc-claude-skill.gitWorks with:
Claude
Overview
About This Skill
AI skill for querying and downloading public cancer imaging data from the National Cancer Institute's Imaging Data Commons. Benefits researchers and healthcare professionals by automating data retrieval for analysis and study.
Setup & Installation
Quick Install
No install command available. Check the GitHub repository for manual installation instructions.
Alternative Install (Git Clone)
git clone https://github.com/ImagingDataCommons/idc-claude-skillRequirements
- Claude Code or compatible AI agent
- Works with: Claude
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Retrieve the latest imaging datasets from the National Cancer Institute's Imaging Data Commons for [COMPANY] focusing on [CANCER_TYPE] research. Provide a summary of the datasets including collection dates, imaging modalities, and patient demographics. Download the top 3 most relevant datasets for [INDUSTRY] analysis.
Example Output
# Imaging Data Summary for Breast Cancer Research ## Top 3 Datasets 1. **TCIA-BRCA-01** - Collection Date: 2020-2022 - Imaging Modalities: MRI, CT - Patient Demographics: 500 female patients, age range 30-75 - Relevance: High relevance for breast cancer screening and diagnosis 2. **TCIA-BRCA-02** - Collection Date: 2018-2020 - Imaging Modalities: Mammography, Ultrasound - Patient Demographics: 300 female patients, age range 40-80 - Relevance: Moderate relevance for breast cancer detection and monitoring 3. **TCIA-BRCA-03** - Collection Date: 2015-2017 - Imaging Modalities: PET, MRI - Patient Demographics: 200 female patients, age range 25-65 - Relevance: Low relevance for breast cancer research due to older data ## Download Links - [TCIA-BRCA-01 Dataset](https://example.com/dataset1) - [TCIA-BRCA-02 Dataset](https://example.com/dataset2) - [TCIA-BRCA-03 Dataset](https://example.com/dataset3)
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