Next-Generation AI Platforms for Predicting Male Infertility: Integrating AI machines for early detection of Male infertility.

To evaluate the hardware architectures, software algorithms, and clinical validation data of emerging artificial intelligence (AI) platforms designed to transform semen analysis from a descriptive snapshot into a prognostic tool for early male fertility decline.

We conducted a targeted technical review (2015-2024) of 24 peer-reviewed publications, alongside analysis of key device specifications and registered clinical trials. Systems were catalogued by imaging modality and analytical engine. Validation data from relevant studies were synthesized to assess diagnostic accuracy and prognostic potential.

Modern platforms, utilizing modalities like high-speed video and digital holography paired with deep learning (e.g., CNNs, LSTMs), extract prognostic biomarkers beyond traditional CASA. These include motility decay kinetics and flagellar beat phenotypes, which correlate with functional deficits like mitochondrial dysfunction. AI models demonstrate high diagnostic concordance (e.g., 96.2% vs. expert morphology). However, robust evidence for long-term fertility prediction is primarily from pilot studies, which link early AI-derived signatures to later subfertility with promising but preliminary accuracy

The technical architecture for AI-driven predictive andrology is advancing rapidly, with systems showing superior diagnostic capability. The principal challenge is transitioning these tools from accurate diagnostics to validated prognostic clinical instruments. Future work must prioritize large-scale, prospective trials to establish clinical utility, paving the way for pre-symptomatic male reproductive health management.