3 citations · 3 across the 4 of their papers we have counts for
5 papers
When Treatments Spill Over: A Neural Framework for Spatiotemporal Causal Effect Estimation
Shaohui Zhang, Jiasheng Shi, Jing Huang
Real-world public health policies are often enacted by local jurisdictions, but their effects can ripple through connected populations. For causal evaluation, this creates a diffic…
Stein-Encoder: A White-Box Supervised Encoder via Stein Identities in Multi-Modal Studies
Jiarui Zhang, Shuoxun Xu, Jiasheng Shi +1
In multi-modal biomedical research, integrating high-dimensional genomic data with clinical baselines is essential for precision medicine. However, standard deep neural network app…
Learning covariate importance for matching in policy-relevant observational research
Hongzhe Zhang, Jiasheng Shi, Jing Huang
Matching methods are widely used to reduce confounding effects in observational studies, but conventional approaches often treat all covariates as equally important, which can resu…
Unlocking the Power of Time-Since-Infection Models: Data Augmentation for Improved Instantaneous Reproduction Number Estimation
Jiasheng Shi, Yizhao Zhou, Jing Huang
The Time Since Infection (TSI) models, which use disease surveillance data to model infectious diseases, have become increasingly popular due to their flexibility and capacity to a…
Early-Phase Local-Area Model for Pandemics Using Limited Data: A SARS-CoV-2 Application
Jiasheng Shi, Jeffrey S. Morris, David M. Rubin +1
The emergence of novel infectious agents presents challenges to statistical models of disease transmission. These challenges arise from limited, poor-quality data and an incomplete…