5 citations · 5 across the 3 of their papers we have counts for
3 papers
Hierarchical infinite factor model for improving the prediction of surgical complications for geriatric patients
Elizabeth Lorenzi, Ricardo Henao, Katherine Heller
We develop a hierarchical infinite latent factor model (HIFM) to appropriately account for the covariance structure across subpopulations in data. We propose a novel Hierarchical D…
Transfer Learning via Latent Factor Modeling to Improve Prediction of Surgical Complications
Elizabeth C Lorenzi, Zhifei Sun, Erich Huang +2
We aim to create a framework for transfer learning using latent factor models to learn the dependence structure between a larger source dataset and a target dataset. The methodolog…
Predictive Hierarchical Clustering: Learning clusters of CPT codes for improving surgical outcomes
Elizabeth C. Lorenzi, Stephanie L. Brown, Zhifei Sun +1
We develop a novel algorithm, Predictive Hierarchical Clustering (PHC), for agglomerative hierarchical clustering of current procedural terminology (CPT) codes. Our predictive hier…