3 papers
eess.IV2023
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis
Changjian Shui, Justin Szeto, Raghav Mehta +2
Trustworthy deployment of deep learning medical imaging models into real-world clinical practice requires that they be calibrated. However, models that are well calibrated overall…
cs.LG2023
Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models
Joshua Durso-Finley, Jean-Pierre Falet, Raghav Mehta +3
Image-based precision medicine aims to personalize treatment decisions based on an individual's unique imaging features so as to improve their clinical outcome. Machine learning fr…
cs.CV2022
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors
Anjun Hu, Jean-Pierre R. Falet, Brennan S. Nichyporuk +4
We propose a hierarchically structured variational inference model for accurately disentangling observable evidence of disease (e.g. brain lesions or atrophy) from subject-specific…