5 citations · 14 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
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…
TRUSWorthy: Toward Clinically Applicable Deep Learning for Confident Detection of Prostate Cancer in Micro-Ultrasound
Mohamed Harmanani, Paul F. R. Wilson, Minh Nguyen Nhat To +6
While deep learning methods have shown great promise in improving the effectiveness of prostate cancer (PCa) diagnosis by detecting suspicious lesions from trans-rectal ultrasound…
Cinepro: Robust Training of Foundation Models for Cancer Detection in Prostate Ultrasound Cineloops
Mohamed Harmanani, Amoon Jamzad, Minh Nguyen Nhat To +11
Prostate cancer (PCa) detection using deep learning (DL) models has shown potential for enhancing real-time guidance during biopsies. However, prostate ultrasound images lack pixel…