
Population-scale reconstruction of menopause dynamics reveals a physiological cliff at the final menstrual period.
Menopause reshapes female physiology, yet current understanding is limited by small longitudinal cohorts that characterize it as a gradual transition. Large-scale biomedical datasets remain underutilized because the final menstrual period (FMP) age is rarely recorded. Here we present a computational framework, inspired by astronomy, that reconstructs FMP-anchored trajectories from cross-sectional data by removing the blurring caused by variation in FMP age across individuals. Applying this to tw
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