8 papers
LLM-Augmented Computational Phenotyping of Long Covid
Jing Wang, Jie Shen, Amar Sra +2
Phenotypic characterization is essential for understanding heterogeneity in chronic diseases and for guiding personalized interventions. Long COVID, a complex and persistent condit…
Predicting Trajectories of Long COVID in Adult Women: The Critical Role of Causal Disentanglement
Jing Wang, Jie Shen, Yiming Luo +3
Early prediction of Post-Acute Sequelae of SARS-CoV-2 severity is a critical challenge for women's health, particularly given the diagnostic overlap between PASC and common hormona…
C-kNN-LSH: A Nearest-Neighbor Algorithm for Sequential Counterfactual Inference
Jing Wang, Jie Shen, Qiaomin Xie +1
Estimating causal effects from longitudinal trajectories is central to understanding the progression of complex conditions and optimizing clinical decision-making, such as comorbid…
Optimal Budgeted Adaptation of Large Language Models
Jing Wang, Jie Shen, Dean Foster +2
The trade-off between labeled data availability and downstream accuracy remains a central challenge in fine-tuning large language models (LLMs). We propose a principled framework f…
Immunological Density Shapes Recovery Trajectories in Long COVID
Jing Wang, Tong Zhang, Xing Niu +6
Post-acute sequelae of SARS-CoV-2 infection (Long COVID) frequently persists for months, yet drivers of clinical remission remain incompletely defined. Here we analyzed 97,564 long…
Metric-Fair Prompting: Treating Similar Samples Similarly
Jing Wang, Jie Shen, Xing Niu +2
We introduce \emph{Metric-Fair Prompting}, a fairness-aware prompting framework that guides large language models (LLMs) to make decisions under metric-fairness constraints. In the…