6 papers
Patients-like-me: A Variational LM--GNN Framework for Explainable Clinical Prediction
Xinyu Wang, Yixuan Li, Hanwei Wu +4
Language models (LMs) offer strong textual representations for electronic health records (EHRs), but they encode patient sequences in isolation and provide limited explainability.…
ragR: Retrieval-Augmented Generation and RAG Assessment in R
Muhammad Aimal Rehman, Zhili Lu, Chi-Kuang Yeh
Retrieval-augmented generation (RAG) combines document retrieval with large language models to produce responses grounded in external evidence. While several R packages support cor…
Single and multi-objective optimal designs for group testing experiments with a focus on screening for an infectious disease
Chi-Kuang Yeh, Weng Kee Wong, Julie Zhou
Group testing techniques are widely used in resource-constrained settings, such as infectious-disease screening, blood safety, DNA library screening, and industrial inspection, whe…
Positive and Unlabeled Data: Model, Estimation, Inference, and Classification
Siyan Liu, Chi-Kuang Yeh, Xin Zhang +2
This study introduces a new approach to addressing positive and unlabeled (PU) data through the double exponential tilting model (DETM). Traditional methods often fall short becaus…
CVXSADes: a stochastic algorithm for constructing optimal exact regression designs with single or multiple objectives
Chi-Kuang Yeh, Julie Zhou
We propose an algorithm to construct optimal exact designs (EDs). Most of the work in the optimal regression design literature focuses on the approximate design (AD) paradigm due t…
Evaluating real-time probabilistic forecasts with application to National Basketball Association outcome prediction
Chi-Kuang Yeh, Gregory Rice, Joel A. Dubin
Motivated by the goal of evaluating real-time forecasts of home team win probabilities in the National Basketball Association, we develop new tools for measuring the quality of con…