42 citations · 145 across the 28 of their papers we have counts for
5 papers · 1 filter
PanelPRO: A R package for multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer
Gavin Lee, Qing Zhang, Jane W. Liang +4
Identifying individuals who are at high risk of cancer due to inherited germline mutations is critical for effective implementation of personalized prevention strategies. Most exis…
Combining Breast Cancer Risk Prediction Models
Zoe Guan, Theodore Huang, Anne Marie McCarthy +6
Accurate risk stratification is key to reducing cancer morbidity through targeted screening and preventative interventions. Numerous breast cancer risk prediction models have been…
Bayesian Combinatorial Multi-Study Factor Analysis
Isabella N. Grabski, Roberta De Vito, Lorenzo Trippa +1
Analyzing multiple studies allows leveraging data from a range of sources and populations, but until recently, there have been limited methodologies to approach the joint unsupervi…
Cross-validation Approaches for Multi-study Predictions
Boyu Ren, Prasad Patil, Francesca Dominici +2
We consider prediction in multiple studies with potential differences in the relationships between predictors and outcomes. Our objective is to integrate data from multiple studies…
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations
Zhun Deng, Frances Ding, Cynthia Dwork +4
We investigate the power of censoring techniques, first developed for learning {\em fair representations}, to address domain generalization. We examine {\em adversarial} censoring…