An Artificial Intelligence-Based Model to Predict Pregnancy After Intrauterine Insemination: A Retrospective Analysis of 9501 Cycles.

ABSTRACT: Background/Objectives: Intrauterine insemination (IUI) is a common first-line approach in the treatment of numerous infertile couples, especially in cases of unexplained infertility. Its relatively low success rate, however, could benefit from the development of AI-based support tools to predict its outcome, thus helping the clinical management of patients undergoing IUI cycles. Our objective was to develop a robust and accurate machine learning model that predicts pregnancy outcomes following IUI. Methods: A retrospective, observational, and single-center study was conducted. In total, 3535 couples (aged 18-43 years) that underwent IUI between January 2011 and December 2015 were recruited. Twenty-one clinical and laboratory parameters of 9501 IUI cycles were used to train di

SUBMITTER: Minano Masip J 

PROVIDER: S-EPMC12300755 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature