Comparative machine learning analysis identifies random forest and adaboost as superior models for the evaluation of semen quality and reproductive hormones
Background Semen analysis is a widely accepted laboratory investigation for evaluating male infertility. However, in cases of idiopathic or unexplained male infertility, comprehensive assessment may require blood-based profiling of a reproductive hormone panel—including follicle-stimulating hormone (FSH), luteinizing h...