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Application of machine learning to predict delayed fecundability among women in sub-Saharan Africa

Delayed fecundability, defined as trying to conceive for ≥12 months without success, is a growing global concern due to the threat of fertility rates falling below the replacement level. This study aimed to predict delayed fecundability and identify influential predictors. Secondary data from recent...

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Autori principali: Meron Asmamaw Alemayehu, Nebiyu Mekonnen Derseh, Tigist Kifle Tsegaw, Tilahun Yemanu Birhan, Banchlay Addis, Berhanie Addis Ayele, Emebet Birhanu Lealem, Eyob Akalewold Alemu, Fetlework Gubena Arage, Gebrie Getu Alemu, Getaneh Awoke Yismaw, Habtamu Abebe Getahun, Habtamu Wagnew Abuhay, Mekuriaw Nibret Aweke
Natura: Artigo
Lingua:Inglês
Pubblicazione: Bioscientifica 2025-10-01
Serie:Reproduction and Fertility
Soggetti:
delayed fecundability
infertility
machine learning
shap analysis
subgroup analysis
interpretable ai
reproductive health
pma data
Accesso online:https://raf.bioscientifica.com/view/journals/raf/6/4/RAF-25-0068.xml
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