28 citations · 37 across the 9 of their papers we have counts for
10 papers
Prediction of mortality and resource utilization in critical care: a deep learning approach using multimodal electronic health records with natural language processing techniques
Yucheng Ruan, Xiang Lan, Daniel J. Tan +2
Background Predicting mortality and resource utilization from electronic health records (EHRs) is challenging yet crucial for optimizing patient outcomes and managing costs in inte…
MEETI: A Multimodal ECG Dataset from MIMIC-IV-ECG with Signals, Images, Features and Interpretations
Deyun Zhang, Xiang Lan, Shijia Geng +4
Electrocardiogram (ECG) plays a foundational role in modern cardiovascular care, enabling non-invasive diagnosis of arrhythmias, myocardial ischemia, and conduction disorders. Whil…
GEM: Empowering MLLM for Grounded ECG Understanding with Time Series and Images
Xiang Lan, Feng Wu, Kai He +3
While recent multimodal large language models (MLLMs) have advanced automated ECG interpretation, they still face two key limitations: (1) insufficient multimodal synergy between t…
Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution
Yucheng Ruan, Xiang Lan, Jingying Ma +3
Tabular data, a prevalent data type across various domains, presents unique challenges due to its heterogeneous nature and complex structural relationships. Achieving high predicti…
Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning
Jihai Zhang, Xiang Lan, Xiaoye Qu +3
Self-Supervised Contrastive Learning has proven effective in deriving high-quality representations from unlabeled data. However, a major challenge that hinders both unimodal and mu…
A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics
Kai He, Rui Mao, Qika Lin +4
The utilization of large language models (LLMs) in the Healthcare domain has generated both excitement and concern due to their ability to effectively respond to freetext queries w…
P-Transformer: A Prompt-based Multimodal Transformer Architecture For Medical Tabular Data
Yucheng Ruan, Xiang Lan, Daniel J. Tan +2
Medical tabular data, abundant in Electronic Health Records (EHRs), is a valuable resource for diverse medical tasks such as risk prediction. While deep learning approaches, partic…
Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
Xiang Lan, Hanshu Yan, Shenda Hong +1
Not all positive pairs are beneficial to time series contrastive learning. In this paper, we study two types of bad positive pairs that can impair the quality of time series repres…
Intra-Inter Subject Self-supervised Learning for Multivariate Cardiac Signals
Xiang Lan, Dianwen Ng, Shenda Hong +1
Learning information-rich and generalizable representations effectively from unlabeled multivariate cardiac signals to identify abnormal heart rhythms (cardiac arrhythmias) is valu…
Identification of 27 abnormalities from multi-lead ECG signals: An ensembled Se-ResNet framework with Sign Loss function
Zhaowei Zhu, Xiang Lan, Tingting Zhao +8
Cardiovascular disease is a major threat to health and one of the primary causes of death globally. The 12-lead ECG is a cheap and commonly accessible tool to identify cardiac abno…