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

This review discusses the potential of microbiome analysis, bacterial extracellular vesicles (BEVs), and artificial intelligence (AI) in improving the diagnosis and management of polycystic ovary syndrome (PCOS), which affects 6–19% of reproductive-age women. Gut dysbiosis and BEVs are highlighted as significant factors in PCOS pathophysiology, with BEVs carrying specific miRNAs and inflammatory proteins that could aid in diagnosis and therapy. AI is noted for its ability to enhance diagnostic accuracy and manage complex datasets, facilitating better phenotypic classification and personalized treatments. The review also addresses ethical concerns like data privacy and algorithmic bias, emphasizing the evolving role of these technologies in developing safer and more effective PCOS interventions.