Progress in the research of artificial intelligence in andrology: a narrative review

Artificial intelligence (AI) is an important branch of computer science. In recent years, it has been widely applied in the healthcare field based on machine learning (ML). The diagnosis and treatment of male disorders face various limitations such as complex etiological and pathological mechanisms, strong subjectivity in diagnosis, limited treatment options, and low patient motivation to seek medical care. This article systematically searches and summarizes the application progress of AI in male infertility (MI), erectile dysfunction (ED), premature ejaculation (PE), and prostatic diseases. The overall goal is to provide a structured reference for the development of intelligent male health diagnosis and treatment systems, and to preliminarily explore the future interdisciplinary research directions in the intersection of AI and andrology.

This review focused on literature from 2010 to 2026 concerning AI and male diseases. This study conducted a search on PubMed, Web of Science, Scopus and China National Knowledge Infrastructure (CNKI) using keywords like "artificial intelligence", "machine learning", "infertility, male", "erectile dysfunction", "premature ejaculation" and "prostatic diseases". Both Chinese and English literature have been included. Reviews, original articles and case reports were searched, and off-topic studies were excluded.

Current research has found that the application of AI covers multiple aspects: participating in clinical laboratory tests through deep learning algorithms; integrating clinical routine indicators for disease risk prediction; developing intelligent medical devices; using imaging to assist in disease differentiation and classification and exploring pathological mechanisms; assisting in each stage of surgery. In addition, large language models (LLMs) and micro-robots are also in their infancy in medical applications.

AI has been introduced into multiple fields of andrology, including MI, ED, PE, and prostatic diseases. This technology demonstrates certain advantages in areas like detection, imaging, intelligent devices, disease prediction, and early screening. However, current research still faces challenges such as data acquisition, model construction, validation methods, regulatory approval, medical reimbursement and ethical norms. Future work should focus more on clinical needs and promote the application of AI in andrology.