Artificial intelligence in urogynecology: literature review

Introduction . Artificial intelligence (AI) is becoming a key tool in modern medicine, enhancing diagnostic accuracy, treatment personalization, and patient management. In urogynecology, the integration of AI opens new opportunities for improving medical image interpretation, urodynamic data analysis, outcome prediction, and remote patient monitoring. Objective . To systematize current evidence on the use of AI technologies in urogynecology, assess their diagnostic and prognostic potential, and outline prospects for their implementation in clinical practice. Materials & methods . A comprehensive search and analysis of Russian and international publications were conducted in eLIBRARY, PubMed, Scopus, and Web of Science databases for the period 2020–2025 using the keywords: urogynecology, female urology, artificial intelligence, machine learning. Studies describing the use of AI in diagnostics, treatment, prognosis, and patient monitoring were included. Results . AI is actively applied for analyzing electronic medical records, interpreting urodynamic tests, and segmenting ultrasound and MRI images, thereby improving the accuracy of diagnosing pelvic organ prolapse and urinary incontinence. In surgical practice, computer vision and augmented reality technologies enhance the precision and safety of operations. Predictive algorithms enable assessment of postoperative complications and recurrence risks, while telemedicine and wearable AI-based systems provide continuous patient monitoring. Despite their promising potential, most models still require additional clinical validation and standardization. Conclusions . The use of AI in urogynecology contributes to improved diagnostic accuracy, personalized treatment, and better clinical outcomes. Broader implementation requires multicenter studies, further algorithm development, and the establishment of ethical and legal frameworks for AI integration into medical practice.