model-validation
Designs and executes validation studies for radiology AI models to ensure clinical reliability and regulatory compliance. Use when user mentions "validate model performance", "external validation", "statistical analysis", "clinical validation", or needs model evaluation.
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- aizech/clinical-skills
- 最近来源活动
- 2026年4月21日 22:11
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SKILL.md
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- model-validation
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- Designs and executes validation studies for radiology AI models to ensure clinical reliability and regulatory compliance. Use when user mentions "validate model performance", "external validation", "statistical analysis", "clinical validation", or needs model evaluation.
# Model Validation Skill
## Triggers
- "validate model performance"
- "external validation"
- "statistical analysis"
- "clinical validation"
- "model comparison"
- "regulatory submission"
- "performance benchmarking"
- "fairness audit"
## Parameters
- `validation_type` (required): Type of validation needed
- `internal` - Retrospective internal dataset
- `external` - Prospective/out-of-distribution testing
- `prospective` - Clinical deployment study
- `regulatory` - FDA/EMA submission prep
- `fairness` - Subgroup disparity analysis
- `comparison` - Head-to-head model comparison
- `model_task` (required): Model's intended use
- `detection` - Sensitivity, specificity, PPV, NPV
- `segmentation` - Dice, IoU, Hausdorff distance
- `classification` - Accuracy, AUC, F1 score
- `regression` - MAE, RMSE, correlation
- `modality` (optional): Imaging modality
- `regulatory_path` (optional): Target clearance pathway
## Validation Framework
### Performance Metrics
| Task | Primary Metrics | Secondary |
|------|-----------------|-----------|
| Detection | Sensitivity, Specificity, AUC | PPV, NPV, FROC |
| Segmentation | Dice, IoU | Hausdorff, ASD |
| Classification | Accuracy, AUC, F1 | Sensitivity, Specificity |
| Regression | MAE, RMSE | Correlation, Bland-Altman |
### Statistical Methods
- Confidence intervals (bootstrap, binominal)
- Significance testing (McNemar, DeLong for AUC)
- Power analysis for sample sizing
- Multiple comparison correction
- Subgroup interaction testing
### Regulatory Standards
- FDA 510(k) predicate comparison
- FDA De Novo requirements
- EU MDR clinical evaluation
- IMDRF clinical evidence framework
- ACR-SIIM AI performance standards
## Output Format
Returns structured JSON with:
- Validation protocol and methodology
- Required sample size with power analysis
- Statistical test selection and rationale
- Results template with standard metrics
- Interpretation guidelines
- Regulatory compliance checklist
## Usage Examples
```
validation_type: external
model_task: detection
modality: CT
validation_type: regulatory
model_task: classification
regulatory_path: 510k
```
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