Uncertainty Estimation Module

The Uncertainty Estimation module quantifies the confidence level of AI-generated predictions to inform clinical decision-making.

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🎯 Purpose

Help clinicians gauge reliability of detected anomalies and classifications, reducing risk of misinterpretation.

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🔍 How It Works

• Uses probabilistic modeling and Bayesian inference techniques.
• Provides confidence intervals, predictive distributions, or entropy measures.
• Flags results with low certainty for further review.

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⚙️ Key Parameters

Parameter	Type	Description	Default
confidence_level	float	Desired confidence threshold (0.0 - 1.0)	0.95
method	string	Estimation technique: bayesian, ensemble, dropout	bayesian

tip

• Choosing a higher confidence level increases caution but may reduce coverage.
• Experiment with different methods for best fit in your clinical setting.

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📦 Output Format

Example:

{
  "uncertainty": 0.12,
  "confidence_interval": [0.75, 0.89],
  "method": "bayesian"
}

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🛠️ Usage Example

curl -X POST "https://api.neolens.ai/v1/uncertainty-estimation" \
  -H "Authorization: Bearer <API_KEY>" \
  -F "image=@scan_mri.png" \
  -F "confidence_level=0.99"

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⚠️ Limitations

• Uncertainty estimates depend on model calibration.
• Interpretation requires clinical context.
• Not a substitute for expert review.