4 papers
UbiQVision: Quantifying Uncertainty in XAI for Image Recognition
Akshat Dubey, Aleksandar Anžel, Bahar İlgen +1
Recent advances in deep learning have led to its widespread adoption across diverse domains, including medical imaging. This progress is driven by increasingly sophisticated model…
UbiQTree: Uncertainty Quantification in XAI with Tree Ensembles
Akshat Dubey, Aleksandar Anžel, Bahar İlgen +1
Explainable Artificial Intelligence (XAI) techniques, such as SHapley Additive exPlanations (SHAP), have become essential tools for interpreting complex ensemble tree-based models,…
Toward Human-Centered Readability Evaluation
Bahar Ä°lgen, Georges Hattab
Text simplification is essential for making public health information accessible to diverse populations, including those with limited health literacy. However, commonly used evalua…
PHAX: A Structured Argumentation Framework for User-Centered Explainable AI in Public Health and Biomedical Sciences
Bahar Ä°lgen, Akshat Dubey, Georges Hattab
Ensuring transparency and trust in AI-driven public health and biomedical sciences systems requires more than accurate predictions-it demands explanations that are clear, contextua…