Citation:
Theodore Huang, Gregory Idos, Christine Hong, Stephen Gruber, Giovanni Parmigiani, and Danielle Braun. 2021. “Extending Models Via Gradient Boosting: An Application to Mendelian Models.” arXiv preprint arXiv:2105.06559.
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Recent Publications
- A validation of models for prediction of pathogenic variants in mismatch repair genes
- Statistical methods for Mendelian models with multiple genes and cancers
- Prediction of hereditary cancers using neural networks
- Validation of Breast Cancer Risk Models by Race/Ethnicity, Family History and Molecular Subtypes
- Extending models via gradient boosting: An application to Mendelian models
- Penetrance of male breast cancer susceptibility genes: a systematic review
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