What question did this study set out to answer?

The aim is to propose a structured evaluation framework to assess the explainability features of AI in medical imaging.

January 18, 2026BioengineeringOpen Access

Evaluating Explainability: A Framework for Systematic Assessment of Explainable AI Features in Medical Imaging

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This framework evaluates explainable AI features in medical imaging, suggesting improved assessment techniques for medical devices.

The aim is to propose a structured evaluation framework to assess the explainability features of AI in medical imaging.
Developed a framework based on four criteria for assessing explainability: consistency, plausibility, fidelity, and usefulness.
Created a scorecard to systematically evaluate AI explainability methods in medical imaging.
Illustrated the framework using Ablation CAM and Eigen CAM on synthetic mammographies for breast lesion detection.
Established a method for quantifying the quality of explanations provided by AI in medical devices.
Demonstrated that the first three criteria can be effectively evaluated in task-relevant scenarios.

Lago et al. (2026) studied this question.

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