6 citations · 6 across the 4 of their papers we have counts for
4 papers
Selective Prediction Reduces the Negative Effects of Automation Bias Overall but Increases False Negatives
Sarah Jabbour, David Fouhey, Nikola Banovic +4
AI has the potential to augment human decision making. However, even high-performing models can produce inaccurate predictions when deployed. These inaccuracies, combined with auto…
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks
Sarah Jabbour, Gregory Kondas, Ella Kazerooni +3
We propose a permutation-based explanation method for image classifiers. Current image-model explanations like activation maps are limited to instance-based explanations in the pix…
Combining chest X-rays and electronic health record (EHR) data using machine learning to diagnose acute respiratory failure
Sarah Jabbour, David Fouhey, Ella Kazerooni +2
Objective: When patients develop acute respiratory failure, accurately identifying the underlying etiology is essential for determining the best treatment. However, differentiating…
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts
Sarah Jabbour, David Fouhey, Ella Kazerooni +2
While deep learning has shown promise in improving the automated diagnosis of disease based on chest X-rays, deep networks may exhibit undesirable behavior related to shortcuts. Th…