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Abstract Objective: To develop and validate interpretable machine-learning models predicting cumulative live birth rate (CLBR) in ART patients. Methods: In this single-center retrospective cohort (January 2019–June 2024), 7,773 oocyte retrieval cycles were analysed. XGBoost gain ranking, applied to all screened cycles with native handling of missing values, selected eight predictors that were complete in every cycle, so no cycle was excluded for missing data.
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