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Found 3 papers, 2 papers with code
Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction
We assess the sensitivity score on a set of representative words in the test set using two classifiers trained for hospital readmission classification with similar performance statistics.
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations
NURD finds a representation from this set that is most informative of the label under the nuisance-randomized distribution, and we prove that this representation achieves the highest performance regardless of the nuisance-label relationship.
Confounding variables can degrade generalization performance of radiological deep learning models
Early results in using convolutional neural networks (CNNs) on x-rays to diagnose disease have been promising, but it has not yet been shown that models trained on x-rays from one hospital or one group of hospitals will work equally well at different hospitals.
