5 citations · 7 across the 3 of their papers we have counts for
4 papers
Sequential algorithmic modification with test data reuse
Jean Feng, Gene Pennello, Nicholas Petrick +3
After initial release of a machine learning algorithm, the model can be fine-tuned by retraining on subsequently gathered data, adding newly discovered features, or more. Each modi…
Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees
Jean Feng, Alexej Gossmann, Berkman Sahiner +1
After deploying a clinical prediction model, subsequently collected data can be used to fine-tune its predictions and adapt to temporal shifts. Because model updating carries risks…
Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift
Xudong Sun, Alexej Gossmann, Yu Wang +1
A novel variational inference based resampling framework is proposed to evaluate the robustness and generalization capability of deep learning models with respect to distribution s…
Multimodal Sparse Classifier for Adolescent Brain Age Prediction
Peyman Hosseinzadeh Kassani, Alexej Gossmann, Yu-Ping Wang
The study of healthy brain development helps to better understand the brain transformation and brain connectivity patterns which happen during childhood to adulthood. This study pr…