4 papers
Uncertainty-Aware Prediction of Parkinson's Disease Medication Needs: A Two-Stage Conformal Prediction Approach
Ricardo Diaz-Rincon, Muxuan Liang, Adolfo Ramirez-Zamora +1
Parkinson's Disease (PD) medication management presents unique challenges due to heterogeneous disease progression and treatment response. Neurologists must balance symptom control…
Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameters
Sohom Bhattacharya, Yongzhuo Chen, Muxuan Liang
In the age of large and heterogeneous datasets, the integration of information from diverse sources is essential to improve parameter estimation. Multi-task learning offers a power…
DeepJ: Graph Convolutional Transformers with Differentiable Pooling for Patient Trajectory Modeling
Deyi Li, Zijun Yao, Muxuan Liang +1
In recent years, graph learning has gained significant interest for modeling complex interactions among medical events in structured Electronic Health Record (EHR) data. However, e…
Penalized Linear Models for Highly Correlated High-Dimensional Immunophenotyping Data
Xiaoru Dong, Apoorva Goyal, Muxuan Liang +3
Accurate prediction and identification of variables associated with outcomes or disease states are critical for advancing diagnosis, prognosis, and precision medicine in biomedical…