127 citations · 242 across the 9 of their papers we have counts for
10 papers
MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data
Yaobin Ling, Xiaoqian Jiang, Yejin Kim
In the era of big data, access to abundant data is crucial for driving research forward. However, such data is often inaccessible due to privacy concerns or high costs, particularl…
Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine
Pulakesh Upadhyaya, Kai Zhang, Can Li +2
Causal structure learning refers to a process of identifying causal structures from observational data, and it can have multiple applications in biomedicine and health care. This p…
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark
Yaobin Ling, Pulakesh Upadhyaya, Luyao Chen +2
Developing new drugs for target diseases is a time-consuming and expensive task, drug repurposing has become a popular topic in the drug development field. As much health claim dat…
Relational graph convolutional networks for predicting blood-brain barrier penetration of drug molecules
Yan Ding, Xiaoqian Jiang, Yejin Kim
Evaluating the blood-brain barrier (BBB) permeability of drug molecules is a critical step in brain drug development. Traditional methods for the evaluation require complicated in…
Drug repurposing for COVID-19 using graph neural network and harmonizing multiple evidence
Kanglin Hsieh, Yinyin Wang, Luyao Chen +5
Amid the pandemic of 2019 novel coronavirus disease (COVID-19) infected by SARS-CoV-2, a vast amount of drug research for prevention and treatment has been quickly conducted, but t…
Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates
Tongtong Huang, Yan Chu, Shayan Shams +7
Objective: We study the influence of local reopening policies on the composition of the infectious population and their impact on future hospitalization and mortality rates. Materi…
From Brain Imaging to Graph Analysis: a study on ADNI's patient cohort
Rui Zhang, Luca Giancardo, Danilo A. Pena +3
In this paper, we studied the association between the change of structural brain volumes to the potential development of Alzheimer's disease (AD). Using a simple abstraction techni…
Combining Representation Learning with Tensor Factorization for Risk Factor Analysis - an application to Epilepsy and Alzheimer's disease
Xiaoqian Jiang, Samden Lhatoo, Guo-Qiang Zhang +2
Existing studies consider Alzheimer's disease (AD) a comorbidity of epilepsy, but also recognize epilepsy to occur more frequently in patients with AD than those without. The goal…
Discriminative Sleep Patterns of Alzheimer's Disease via Tensor Factorization
Yejin Kim, Xiaoqian Jiang, Luyao Chen +2
Sleep change is commonly reported in Alzheimer's disease (AD) patients and their brain wave studies show decrease in dreaming and non-dreaming stages. Although sleep disturbance is…
Federated Tensor Factorization for Computational Phenotyping
Yejin Kim, Jimeng Sun, Hwanjo Yu +1
Tensor factorization models offer an effective approach to convert massive electronic health records into meaningful clinical concepts (phenotypes) for data analysis. These models…