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Found 3 papers, 2 papers with code
Confounding Feature Acquisition for Causal Effect Estimation
Reliable treatment effect estimation from observational data depends on the availability of all confounding information.
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III
Robust machine learning relies on access to data that can be used with standardized frameworks in important tasks and the ability to develop models whose performance can be reasonably reproduced.
Ranked #3 on
Length-of-Stay prediction
on MIMIC-III
Reproducibility in Machine Learning for Health
Machine learning algorithms designed to characterize, monitor, and intervene on human health (ML4H) are expected to perform safely and reliably when operating at scale, potentially outside strict human supervision.
