2 citations · 2 across the 5 of their papers we have counts for
5 papers
Topical Hidden Genome: Discovering Latent Cancer Mutational Topics using a Bayesian Multilevel Context-learning Approach
Saptarshi Chakraborty, Zoe Guan, Colin B. Begg +1
Statistical inference on the cancer-site specificities of collective ultra-rare whole genome somatic mutations is an open problem. Traditional statistical methods cannot handle who…
Prediction of Hereditary Cancers Using Neural Networks
Zoe Guan, Giovanni Parmigiani, Danielle Braun +1
Family history is a major risk factor for many types of cancer. Mendelian risk prediction models translate family histories into cancer risk predictions based on knowledge of cance…
A Proper Scoring Rule for Validation of Competing Risks Models
Zoe Guan
Scoring rules are used to evaluate the quality of predictions that take the form of probability distributions. A scoring rule is strictly proper if its expected value is uniquely m…
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…
Merging versus Ensembling in Multi-Study Prediction: Theoretical Insight from Random Effects
Zoe Guan, Giovanni Parmigiani, Prasad Patil
A critical decision point when training predictors using multiple studies is whether studies should be combined or treated separately. We compare two multi-study prediction approac…