Innovative Research on an AI-Integrated Full-Cycle Intelligent Management System for Donor Semen Specimens in Human Sperm Banks

Abstract

With the rapid advancement of assisted reproductive technologies (ART), human sperm banks urgently require a transition from traditional management models to intelligent, data-driven systems. This study proposes a full-cycle status management system that deeply integrates artificial intelligence (AI) with an information platform. By combining machine learning, natural language processing (NLP), the Internet of Things (IoT), and blockchain technology, the system automates and optimizes the entire workflow from donor screening to clinical application. An AI-driven predictive model enhances semen quality assessment, dynamic data analysis improves follow-up efficiency, and multi-center clinical trials validate its effectiveness. Results demonstrate a 35% improvement in management efficiency, a 25% reduction in operational costs, and a 12% increase in pregnancy success rates. This research provides an innovative solution for intelligent management in reproductive medicine and highlights the broad potential of AI in biological specimen repository management.