Harnessing Microbiome, Bacterial Extracellular Vesicle, and Artificial Intelligence for Polycystic Ovary Syndrome Diagnosis and Management

This review explores the integration of microbiome analysis, bacterial extracellular vesicles (BEVs), and artificial intelligence (AI) to improve the diagnosis and management of Polycystic Ovary Syndrome (PCOS), which affects 6-19% of women of reproductive age. The gut microbiome's role in PCOS pathogenesis is highlighted, with studies showing specific microbial changes in PCOS patients. AI, particularly machine learning, enhances diagnostic accuracy by analyzing complex datasets, achieving high accuracy in studies, such as 92.9% in a study with 721 women. This integrated approach could lead to more personalized treatment strategies, although challenges like data privacy and AI bias need addressing.