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06/01/2023
Multi-study R-learner for Heterogeneous Treatment Effect Estimation
Estimating heterogeneous treatment effects is crucial for informing pers...
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04/30/2023
Defining Replicability of Prediction Rules
In this article I propose an approach for defining replicability for pre...
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04/04/2023
Bayesian Meta-Analysis of Penetrance for Cancer Risk
Multi-gene panel testing allows many cancer susceptibility genes to be t...
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12/16/2022
Multi-Task Learning for Sparsity Pattern Heterogeneity: A Discrete Optimization Approach
We extend best-subset selection to linear Multi-Task Learning (MTL), whe...
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07/11/2022
Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensembling
Cross-study replicability is a powerful model evaluation criterion that ...
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02/03/2022
Cross-Study Replicability in Cluster Analysis
In cancer research, clustering techniques are widely used for explorator...
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09/19/2021
Optimal Ensemble Construction for Multi-Study Prediction with Applications to COVID-19 Excess Mortality Estimation
It is increasingly common to encounter prediction tasks in the biomedica...
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08/27/2021
PanelPRO: a general framework for multi-gene, multi-cancer Mendelian risk prediction models
Risk evaluation to identify individuals who are at greater risk of cance...
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06/25/2021
Prediction of Hereditary Cancers Using Neural Networks
Family history is a major risk factor for many types of cancer. Mendelia...
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05/17/2021
Cross-Cluster Weighted Forests
Adapting machine learning algorithms to better handle the presence of na...
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05/13/2021
Extending Models Via Gradient Boosting: An Application to Mendelian Models
Improving existing widely-adopted prediction models is often a more effi...
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10/25/2020
PanelPRO: A R package for multi-syndrome, multi-gene risk modeling for individuals with a family history of cancer
Identifying individuals who are at high risk of cancer due to inherited ...
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07/31/2020
Combining Breast Cancer Risk Prediction Models
Accurate risk stratification is key to reducing cancer morbidity through...
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07/24/2020
Cross-study learning for generalist and specialist predictions
Jointly using data from multiple similar sources for the training of pre...
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07/24/2020
Bayesian Combinatorial Multi-Study Factor Analysis
Analyzing multiple studies allows leveraging data from a range of source...
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06/20/2020
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations
We investigate the power of censoring techniques, first developed for le...
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05/17/2019
Merging versus Ensembling in Multi-Study Machine Learning: Theoretical Insight from Random Effects
A critical decision point when training predictors using multiple studie...
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04/24/2019
Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes
PURPOSE: The medical literature relevant to germline genetics is growing...
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03/04/2019
The Fuzzy ROC
The fuzzy ROC extends Receiver Operating Curve (ROC) visualization to th...
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06/26/2018