Addressing bias in feature importances derived from XGBoost. Response to Br J Anaesth 2025;134:613-5

Dor Atias; Uri Obolski

doi:10.1016/j.bja.2025.01.022

Addressing bias in feature importances derived from XGBoost. Response to Br J Anaesth 2025;134:613-5

Dor Atias, Uri Obolski^*

^*Corresponding author for this work

School of Public Health

Maccabi Healthcare Services

Research output: Contribution to journal › Letter › peer-review

Original language	English
Pages (from-to)	1267
Number of pages	1
Journal	British Journal of Anaesthesia
Volume	134
Issue number	4
DOIs	https://doi.org/10.1016/j.bja.2025.01.022
State	Published - Apr 2025

Keywords

SHAP analysis
artificial intelligence
bias
machine learning
opioid use

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10.1016/j.bja.2025.01.022

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Addressing bias in feature importances derived from XGBoost. Response to Br J Anaesth 2025;134:613-5

Keywords

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