5 citations · 16 across the 13 of their papers we have counts for
3 papers · 1 filter
Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventions
Jean Feng, Alexej Gossmann, Gene Pennello +3
Performance monitoring of machine learning (ML)-based risk prediction models in healthcare is complicated by the issue of confounding medical interventions (CMI): when an algorithm…
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…