6 citations · 7 across the 5 of their papers we have counts for
5 papers
MIMIC: A Generative Multimodal Foundation Model for Biomolecules
Siavash Golkar, Jake Kovalic, Irina Espejo Morales +28
Biological function emerges from coupled constraints across sequence, structure, regulation, evolution, and cellular context, yet most foundation models in biology are trained with…
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…