Jean Feng | DeepAI

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∙ 07/28/2023

Is this model reliable for everyone? Testing for strong calibration

In a well-calibrated risk prediction model, the average predicted probab...

0 Jean Feng, et al. ∙

∙ 11/17/2022

Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventions

Monitoring the performance of machine learning (ML)-based risk predictio...

0 Jean Feng, et al. ∙

∙ 03/21/2022

Sequential algorithmic modification with test data reuse

After initial release of a machine learning algorithm, the model can be ...

0 Jean Feng, et al. ∙

∙ 10/13/2021

Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees

After deploying a clinical prediction model, subsequently collected data...

0 Jean Feng, et al. ∙

∙ 12/14/2020

Learning how to approve updates to machine learning algorithms in non-stationary settings

Machine learning algorithms in healthcare have the potential to continua...

0 Jean Feng, et al. ∙

∙ 06/16/2020

Efficient nonparametric statistical inference on population feature importance using Shapley values

The true population-level importance of a variable in a prediction task ...

0 Brian D. Williamson, et al. ∙

∙ 05/11/2020

Ensembled sparse-input hierarchical networks for high-dimensional datasets

Neural networks have seen limited use in prediction for high-dimensional...

0 Jean Feng, et al. ∙

∙ 12/28/2019

Approval policies for modifications to Machine Learning-Based Software as a Medical Device: A study of bio-creep

Successful deployment of machine learning algorithms in healthcare requi...

0 Jean Feng, et al. ∙

∙ 06/13/2019

Selective prediction-set models with coverage guarantees

Though black-box predictors are state-of-the-art for many complex tasks,...

0 Jean Feng, et al. ∙

∙ 03/29/2019

Estimation of cell lineage trees by maximum-likelihood phylogenetics

CRISPR technology has enabled large-scale cell lineage tracing for compl...

0 Jean Feng, et al. ∙

∙ 03/28/2019

An analysis of the cost of hyper-parameter selection via split-sample validation, with applications to penalized regression

In the regression setting, given a set of hyper-parameters, a model-esti...

0 Jean Feng, et al. ∙

∙ 11/21/2017

Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification

Neural networks are usually not the tool of choice for nonparametric hig...

0 Jean Feng, et al. ∙

∙ 11/11/2017

Survival analysis of DNA mutation motifs with penalized proportional hazards

Antibodies, an essential part of our immune system, develop in an intric...

0 Jean Feng, et al. ∙

∙ 03/28/2017

Gradient-based Regularization Parameter Selection for Problems with Non-smooth Penalty Functions

In high-dimensional and/or non-parametric regression problems, regulariz...

0 Jean Feng, et al. ∙

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