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 • 15 Mar 2024 • Wenrui Fan, Mohammod Naimul Islam Suvon, Shuo Zhou, Xianyuan Liu, Samer Alabed, Venet Osmani, Andrew Swift, Chen Chen, Haiping Lu
Moreover, a novel vision-language Prototypical Contr-astive Learning (ProtoCL) method is adopted in MeDSLIP to enhance the alignment within the anatomical and pathological streams.
no code implementations • 1 Sep 2023 • Peizhen Bai, Xianyuan Liu, Haiping Lu
Owing to the scarcity of labeled molecules, there has been growing interest in self-supervised learning methods that learn generalizable molecular representations from unlabeled data.
no code implementations • 17 Aug 2021 • Xianyuan Liu, Shuo Zhou, Tao Lei, Haiping Lu
Finally, we propose a Channel-Temporal Attention Network (CTAN) to integrate these blocks into existing architectures.
no code implementations • 22 Jun 2021 • Xianyuan Liu, Raivo Koot, Shuo Zhou, Tao Lei, Haiping Lu
Under the team name xy9, our submission achieved 5th place in terms of top-1 accuracy for verb class and all top-5 accuracies.
1 code implementation • 17 Jun 2021 • Haiping Lu, Xianyuan Liu, Robert Turner, Peizhen Bai, Raivo E Koot, Shuo Zhou, Mustafa Chasmai, Lawrence Schobs
Machine learning is a general-purpose technology holding promises for many interdisciplinary research problems.