12 citations · 24 across the 6 of their papers we have counts for
10 papers
AKI-BERT: a Pre-trained Clinical Language Model for Early Prediction of Acute Kidney Injury
Chengsheng Mao, Liang Yao, Yuan Luo
Acute kidney injury (AKI) is a common clinical syndrome characterized by a sudden episode of kidney failure or kidney damage within a few hours or a few days. Accurate early predic…
Distribution Preserving Graph Representation Learning
Chengsheng Mao, Yuan Luo
Graph neural network (GNN) is effective to model graphs for distributed representations of nodes and an entire graph. Recently, research on the expressive power of GNN attracted gr…
Towards Expressive Graph Representation
Chengsheng Mao, Liang Yao, Yuan Luo
Graph Neural Network (GNN) aggregates the neighborhood of each node into the node embedding and shows its powerful capability for graph representation learning. However, most exist…
A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports
Yikuan Li, Hanyin Wang, Yuan Luo
Joint image-text embedding extracted from medical images and associated contextual reports is the bedrock for most biomedical vision-and-language (V+L) tasks, including medical vis…
Open-Set Recognition with Gaussian Mixture Variational Autoencoders
Alexander Cao, Yuan Luo, Diego Klabjan
In inference, open-set classification is to either classify a sample into a known class from training or reject it as an unknown class. Existing deep open-set classifiers train exp…
Med2Meta: Learning Representations of Medical Concepts with Meta-Embeddings
Shaika Chowdhury, Chenwei Zhang, Philip S. Yu +1
Distributed representations of medical concepts have been used to support downstream clinical tasks recently. Electronic Health Records (EHR) capture different aspects of patients'…