Singapore-Korea AI Study Uncovers Hidden Male Infertility

A new study conducted in South Korea and Singapore is developing an AI-guided method to detect hidden infertility in Asian men. Led by Dr. Huang Zhongwei, adjunct assistant professor and deputy director at the National University of Singapore’s Bia-Echo Asia Centre for Reproductive Longevity and Equality, in collaboration with Associate Professor Lee Jae Ho from CHA University in South Korea, the project aims to create a diagnostic tool to identify male infertility more accurately.

The research team analyzed retrospective data from Korean couples undergoing in-vitro fertilization (IVF), including clinical and embryological data, semen analyses, sperm images, and computer-assisted sperm assessments. Using AI-assisted data analysis, they discovered a correlation between specific sperm motility patterns and embryonic aneuploidy in resulting zygotes, achieving around 70% diagnostic accuracy. This finding could help explain cases of unexplained male infertility and assist doctors in deciding when to use preimplantation genetic testing for aneuploidy (PGT-A) during IVF.

The researchers are now preparing for a prospective study pending approval from the Korean Ministry of Food and Drug Safety and plan to validate their findings across Asian populations. Dr. Huang emphasized the need to build robust fertility datasets for Asian men, as data in this area remain limited. He noted that a comprehensive assessment of male reproductive potential must integrate validation data, semen analyses, and medical histories.

The team also envisions the potential translation of their AI model into a diagnostic device for clinical use. If accuracy holds in real-world settings, the technology could be registered as a new medical tool for diagnosing male infertility. Dr. Huang described the model as an adjunct to fertility management, supporting clinicians in optimizing reproductive outcomes for couples.

Male infertility contributes to nearly half of all fertility challenges worldwide, yet it remains underdiagnosed and undertreated. Dr. Huang’s collaboration with CHA University stems from a shared goal to improve diagnostic precision and address the complex causes of male infertility through AI-driven insights. In parallel, researchers in Hong Kong have developed a separate AI model that identifies sperm fertility potential by analyzing sperm binding ability, demonstrating over 96% clinical accuracy—part of a growing trend of applying AI to reproductive health.

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