no code implementations • 20 Mar 2024 • Mohammod N. I. Suvon, Prasun C. Tripathi, Wenrui Fan, Shuo Zhou, Xianyuan Liu, Samer Alabed, Venet Osmani, Andrew J. Swift, Chen Chen, Haiping Lu
In response to these limitations, we propose a novel multimodal variational autoencoder ($\text{CardioVAE}_\text{X, G}$) to integrate low-cost chest X-ray (CXR) and electrocardiogram (ECG) modalities with pre-training on a large unlabeled dataset.
no code implementations • 20 Mar 2023 • Michael J. Sharkey, Krit Dwivedi, Samer Alabed, Andrew J. Swift
This study aims to develop an artificial intelligence (AI) deep learning model for lung texture classification in CT Pulmonary Angiography (CTPA), and evaluate its correlation with clinical assessment methods.
1 code implementation • 14 Mar 2023 • Prasun C. Tripathi, Mohammod N. I. Suvon, Lawrence Schobs, Shuo Zhou, Samer Alabed, Andrew J. Swift, Haiping Lu
In this work, we develop a tensor learning-based pipeline for identifying PAWP from multimodal cardiac Magnetic Resonance Imaging (MRI).
2 code implementations • 4 Mar 2022 • Lawrence Schobs, Andrew J. Swift, Haiping Lu
We propose Quantile Binning, a data-driven method to categorize predictions by uncertainty with estimated error bounds.
no code implementations • 8 Apr 2021 • Michail Mamalakis, Andrew J. Swift, Bart Vorselaars, Surajit Ray, Simonne Weeks, Weiping Ding, Richard H. Clayton, Louise S. Mackenzie, Abhirup Banerjee
The global pandemic of COVID-19 is continuing to have a significant effect on the well-being of global population, increasing the demand for rapid testing, diagnosis, and treatment.