Archer Yi Yang

Deep Learning for Cognitive Task Presence Prediction from Dynamic Functional Connectivity

This study evaluates how deep learning models and dynamic functional connectivity estimation methods affect task presence prediction from fMRI data.

Sparse Polygenic Risk Score Inference with the Spike-and-Slab LASSO

This paper introduces SSLPRS, a Polygenic Risk Score method using Spike-and-Slab LASSO, showing improved variable selection and prediction accuracy over existing methods.

A novel and efficient machine learning Mendelian randomization estimator applied to predict the safety and efficacy of sclerostin inhibition

This paper introduces a machine learning Mendelian randomization estimator, Quantile IV, to assess the causal effects of sclerostin inhibition on bone and cardiovascular outcomes using UK Biobank data.

A Sparse Additive Model for High-Dimensional Interactions with an Exposure Variable

The paper introduces a method called sail to detect non-linear interactions between a key exposure variable and high-dimensional data, showing it outperforms existing methods in prediction and support recovery.