activity
20182026
most citedTRUSWorthy: Toward Clinically Applicable Deep Learning for Confident Detection of Prostate Cancer in Micro-Ultrasound

5 citations · 14 across the 13 of their papers we have counts for

collaborators

15 papers

cs.CV2026

Vision-Language Models Encode Clinical Guidelines for Concept-Based Medical Reasoning

Mohamed Harmanani, Bining Long, Zhuoxin Guo +6

Concept Bottleneck Models (CBMs) are a prominent framework for interpretable AI that map learned visual features to a set of meaningful concepts for task-specific downstream predic…

cs.CV2026

GUIDE-US: Grade-Informed Unpaired Distillation of Encoder Knowledge from Histopathology to Micro-UltraSound

Emma Willis, Tarek Elghareb, Paul F. R. Wilson +6

Purpose: Non-invasive grading of prostate cancer (PCa) from micro-ultrasound (micro-US) could expedite triage and guide biopsies toward the most aggressive regions, yet current mod…

eess.IV2025

ProstNFound+: A Prospective Study using Medical Foundation Models for Prostate Cancer Detection

Paul F. R. Wilson, Mohamed Harmanani, Minh Nguyen Nhat To +7

Purpose: Medical foundation models (FMs) offer a path to build high-performance diagnostic systems. However, their application to prostate cancer (PCa) detection from micro-ultraso…

cs.CV2025★ 2 cited

TREAT-Net: Tabular-Referenced Echocardiography Analysis for Acute Coronary Syndrome Treatment Prediction

Diane Kim, Minh Nguyen Nhat To, Sherif Abdalla +3

Coronary angiography remains the gold standard for diagnosing Acute Coronary Syndrome (ACS). However, its resource-intensive and invasive nature can expose patients to procedural r…

cs.LG2025

Domain Knowledge is Power: Leveraging Physiological Priors for Self Supervised Representation Learning in Electrocardiography

Nooshin Maghsoodi, Sarah Nassar, Paul F R Wilson +7

Objective: Electrocardiograms (ECGs) play a crucial role in diagnosing heart conditions; however, the effectiveness of artificial intelligence (AI)-based ECG analysis is often hind…

cs.LG2025

Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift

Minh Nguyen Nhat To, Paul F RWilson, Viet Nguyen +6

The subpopulationtion shift, characterized by a disparity in subpopulation distributibetween theween the training and target datasets, can significantly degrade the performance of…