3 papers
cs.CV2026
A Calibrated Memorization Index (MI) for Detecting Training Data Leakage in Generative MRI Models
Yash Deo, Yan Jia, Toni Lassila +5
Image generative models are known to duplicate images from the training data as part of their outputs, which can lead to privacy concerns when used for medical image generation. We…
cs.CL2026
WER is Unaware: Assessing How ASR Errors Distort Clinical Understanding in Patient Facing Dialogue
Zachary Ellis, Jared Joselowitz, Yash Deo +7
As Automatic Speech Recognition (ASR) is increasingly deployed in clinical dialogue, standard evaluations still rely heavily on Word Error Rate (WER). This paper challenges that st…
eess.IV2025
Metrics that matter: Evaluating image quality metrics for medical image generation
Yash Deo, Yan Jia, Toni Lassila +5
Evaluating generative models for synthetic medical imaging is crucial yet challenging, especially given the high standards of fidelity, anatomical accuracy, and safety required for…