Clinical Interpretability: Saliency Maps and Calibrated Confidence Intervals

Empowering physicians to trust algorithmic decisions with transparent visual and statistical explanations.

True Pixel Attribution vs Spurious Artifacts

Standard saliency methods often highlight imaging borders or hospital hospital-bed metal clips rather than pathological lesions. Integrated Gradients and Guided Grad-CAM++ ensure attribution maps strictly highlight anatomical abnormalities.

Uncertainty Quantification in Critical Care

Providing doctors with a bare probability percentage without epistemic uncertainty is hazardous. The platform couples predictions with Monte Carlo Dropout uncertainty bounds, urging human review when uncertainty is elevated.

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