radiology-dataset-guide
Guides researchers and developers through radiology dataset selection, access, and utilization for AI development. Use when user mentions "radiology dataset", "medical imaging data", "RSNA challenge", "MIMIC data access", or needs dataset guidance.
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- aizech/clinical-skills
- Letzte Quellaktivität
- 21. April 2026 um 22:11
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- Englisch
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- 5
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- 1
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- name
- radiology-dataset-guide
- description
- Guides researchers and developers through radiology dataset selection, access, and utilization for AI development. Use when user mentions "radiology dataset", "medical imaging data", "RSNA challenge", "MIMIC data access", or needs dataset guidance.
# Radiology Dataset Guide Skill
## Triggers
- "radiology dataset"
- "medical imaging data"
- "RSNA challenge"
- "MIMIC data access"
- "CheXpert download"
- "dataset comparison"
- "training data preparation"
- "public dataset"
## Parameters
- `task_type` (required): ML/AI task being solved
- `detection` - Abnormality/nodule/cancer detection
- `segmentation` - Organ or lesion segmentation
- `classification` - Disease or finding classification
- `reconstruction` - Image reconstruction/enhancement
- `quantification` - Measurement and feature extraction
- `anatomy` (optional): Body region or organ system
- `modality` (optional): Imaging modality preference
- `access_requirements` (optional): Data use restrictions
- `commercial_use` (optional): Boolean for commercial application intent
## Dataset Inventory
| Dataset | Modality | Primary Task | Access | Annotations |
|---------|----------|---------------|--------|-------------|
| RSNA Bone Age | X-ray | Regression | Public | Age, quality |
| RSNA Pneumonia | Chest X-ray | Detection | Public | Bounding boxes |
| RSNA Brain Hemorrhage | CT | Detection | Public | Bounding boxes, type |
| NIH ChestX-ray14 | Chest X-ray | Classification | Public | Labels |
| CheXpert | Chest X-ray | Classification | Institutional | Labels |
| MIMIC-CXR | Chest X-ray | Multi | PhysioNet | Labels, reports |
| CheXphoto | Chest X-ray | Classification | Public | Synth/real pairs |
| LUNA16 | CT | Detection | Public | Nodule centers |
| KiTS | CT | Segmentation | Public | Kidney/tumor |
| BraTS | MRI | Segmentation | Research | Multi-modal seg |
| PANDA | Histology | Classification | Public | Biopsy grades |
| OBJ-CXR | Chest X-ray | Detection | Public | Bounding boxes |
## Output Format
Returns structured JSON with:
- Relevant datasets ranked by suitability
- Annotation quality and completeness
- Access procedure and requirements
- Key publications and benchmarks
- Preprocessing recommendations
- Compliance and ethics considerations
## Usage Examples
```
task_type: detection
anatomy: lung
modality: CT
task_type: classification
anatomy: chest
commercial_use: true
```
Auf GitHub ansehen