8 papers
A Dataset and Benchmarks for Atrial Fibrillation Detection from Electrocardiograms of Intensive Care Unit Patients
Sarah Nassar, Nooshin Maghsoodi, Sophia Mannina +7
Objective: Atrial fibrillation (AF) is the most common cardiac arrhythmia experienced by intensive care unit (ICU) patients and can cause adverse health effects. In this study, we…
To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models
Jiayun Luo, Wan-Cyuan Fan, Lyuyang Wang +4
Large Vision Language Models (LVLMs) have recently emerged as powerful architectures capable of understanding and reasoning over both visual and textual information. These models t…
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…
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…