4 citations · 4 across the 6 of their papers we have counts for
6 papers
Responsible Integration of AI in Cancer Genomics: Barriers, Risks, and Pathways to Trustworthy Clinical Translation
Bahar İlgen, Yiannos Tolias, Denise Kühnert +5
Artificial intelligence (AI) and natural language processing (NLP) are increasingly used to extract, integrate, and interpret biomedical knowledge relevant to cancer genomics, yet…
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…
Toward Human-Centered Readability Evaluation
Bahar İlgen, 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…
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,…
PHAX: A Structured Argumentation Framework for User-Centered Explainable AI in Public Health and Biomedical Sciences
Bahar İlgen, 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…
Kernel-based Learning for Safe Control of Discrete-Time Unknown Systems under Incomplete Observations
Zewen Yang, Xiaobing Dai, Weijie Yang +3
Safe control for dynamical systems is critical, yet the presence of unknown dynamics poses significant challenges. In this paper, we present a learning-based control approach for t…