Development and validation of questionnaire-based machine-learning models to predict early natural menopause: a national cross-sectional study
Abstract This epidemiological survey recruited 18,015 postmenopausal women aged 36–60 in 13 cities across 12 provinces in China. Ten machine learning algorithms were evaluated, with the optimal model was selected by area under the curve (AUC). The Boruta algorithm identified 70 predictive factors, w...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | npj Women's Health |
| Online Access: | https://doi.org/10.1038/s44294-025-00098-4 |
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