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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.
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Reproducibility in Machine Learning for Health
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Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. In In Press: Machine Learning for Healthcare Conference (MLHC)
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