Artificial Intelligence in Andrology: A New Frontier in Male Infertility Diagnosis and Treatment.

Abstract

Purpose of review: Infertility affects approximately 15% of couples globally, with male-factor infertility contributing to about half of these cases. Despite advancements in reproductive medicine, particularly in surgical methods, the prevalence of male infertility remains high and underreported, often due to cultural stigmas. Traditional semen analysis, a crucial component in diagnosing male infertility, involves subjective assessments, leading to variability in results. This review explores the advancements and applications of Artificial Intelligence (AI) in diagnosing and treating male infertility, emphasizing its potential to revolutionize the field by providing reliable and efficient diagnostic tools and improving treatment outcomes.

Recent findings: Recent advances in reproductive medicine, including techniques like microdissection testicular sperm extraction and intracytoplasmic sperm injection, have improved conception rates. However, the integration of AI in andrology offers even greater promise. AI techniques, including machine learning and artificial neural networks, now provide automated and objective analysis of sperm motility, and DNA integrity, significantly improving diagnostic precision. These technologies outperform traditional methods by reducing subjectivity in sperm evaluation, identifying subtle abnormalities often missed during manual assessments, and enhancing the selection process for assisted reproductive technologies. Moreover, AI-based predictive models optimize patient selection and personalize treatment protocols, increasing success rates. AI-driven technologies hold transformative potential in the field of reproductive medicine by enhancing the accuracy and efficiency of diagnosing and treating male infertility. The automated and objective analysis offered by AI can offer the possibilities of achieving parenthood for infertile men. However, the implementation of these technologies must be carefully managed, with particular attention to ethical considerations such as bias, transparency, and data privacy. AI's role in advancing reproductive medicine is promising, but responsible deployment is essential to maximize its benefits.