Yeliz Kaya

ORCID: 0000-0003-4277-3960 · 1 paper in corpus
other 2025
Reproductive sciences (Thousand Oaks, Calif.) ·doi:10.1007/s43032-025-01927-2

This study aimed to predict the likelihood of natural conception among couples by using a machine learning (ML) approach based on sociodemographic and sexual health data. This marks a novel, non-invasive methodology for fertility prediction…