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Found 3 papers, 2 papers with code
ED-Copilot: Reduce Emergency Department Wait Time with Language Model Diagnostic Assistance
Using publicly available patient data, we collaborate with ED clinicians to curate MIMIC-ED-Assist, a benchmark that measures the ability of AI systems in suggesting laboratory tests that minimize ED wait times, while correctly predicting critical outcomes such as death.
Group Probability-Weighted Tree Sums for Interpretable Modeling of Heterogeneous Data
Machine learning in high-stakes domains, such as healthcare, faces two critical challenges: (1) generalizing to diverse data distributions given limited training data while (2) maintaining interpretability.
Fast Interpretable Greedy-Tree Sums
In such settings, practitioners often use highly interpretable decision tree models, but these suffer from inductive bias against additive structure.
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