no code implementations • 2 Oct 2022 • Prashnna K Gyawali, Xiaoxia Liu, James Zou, Zihuai He
Despite extensive recent efforts to define different feature importance metrics for deep learning models, we identified that inherent stochasticity in the design and training of deep learning models makes commonly used feature importance scores unstable.
no code implementations • 10 May 2022 • Prashnna K Gyawali, Yann Le Guen, Xiaoxia Liu, Hua Tang, James Zou, Zihuai He
This can lead to biases in the risk predictors resulting in poor generalization when applied to minority populations and admixed individuals such as African Americans.
1 code implementation • 29 Sep 2021 • Peyman H. Kassani, Fred Lu, Yann Le Guen, Zihuai He
The merit of the proposed method includes: (1) flexible modelling of the non-linear effect of genetic variants to improve statistical power; (2) multiple knockoffs in the input layer to rigorously control false discovery rate; (3) hierarchical layers to substantially reduce the number of weight parameters and activations to improve computational efficiency; (4) de-randomized feature selection to stabilize identified signals.