urovestВестник урологииUrology Herald2308-6424Rostov State Medical University10.21886/2308-6424-2026-14-1-83-92urovest-1190Research ArticleОБЗОРЫ ЛИТЕРАТУРЫREVIEWS ARTICLEИскусственный интеллект в урогинекологии: обзор литературыArtificial intelligence in urogynecology: literature reviewhttps://orcid.org/0009-0004-0634-088XЛазареваЕ. К.LazarevaE. K.

Елена Константиновна Лазарева

Москва

Elena K. Lazareva

Moscow

christovskaya@ya.ruhttps://orcid.org/0009-0002-2246-0510ЮмакуловА. Х.IumakulovA. K.

Адиль Хафизович Юмакулов

Москва

Adil K. Iumakulov

Moscow

adiljumakulov2000@yahoo.comhttps://orcid.org/0000-0001-8684-9336ГвоздевМ. Ю.GvozdevM. Yu.

Михаил Юрьевич Гвоздев — д-р мед. наук

Москва

Michael Yu. Gvozdev — Dr.Sc.(Med)

Moscow

m.gvozdev@mail.ruРоссийский университет медициныРоссияRussian University Of MedicineRussian FederationМосковский многопрофильный научно-клинический центр им. С.П. БоткинаРоссияBotkin Moscow Multidisciplinary Research and Clinical CentreRussian FederationРоссийский университет медицины; Московский многопрофильный научно-клинический центр им. С.П. БоткинаРоссияRussian University Of Medicine; Botkin Moscow Multidisciplinary Research and Clinical CentreRussian Federation2026050420261418392Copyright © Лазарева Е.К., Юмакулов А.Х., Гвоздев М.Ю., 20262026Лазарева Е.К., Юмакулов А.Х., Гвоздев М.Ю.Lazareva E.K., Iumakulov A.K., Gvozdev M.Y.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.urovest.ru/jour/article/view/1190Введение

Введение. Искусственный интеллект (ИИ) становится ключевым инструментом современной медицины, способствующим повышению точности диагностики, персонализации лечения и оптимизации ведения пациентов. В урогинекологии внедрение ИИ открывает новые возможности для решения задач, связанных с интерпретацией медицинских изображений, анализом уродинамических исследований, прогнозированием исходов и дистанционным мониторингом пациенток.

Цель исследования

Цель исследования. Систематизировать современные данные о применении технологий ИИ в урогинекологии, оценить их диагностический и прогностический потенциал, а также определить перспективы внедрения в клиническую практику.

Материалы и методы

Материалы и методы. Проведён поиск и анализ отечественных и зарубежных публикаций в базах eLIBRARY, PubMed, Scopus и Web of Science за 2020 – 2025 годы с использованием ключевых слов: “urogynecology”, “female urology”, “artificial intelligence”, “machine learning”. В обзор включены исследования, описывающие применение ИИ для диагностики, лечения, прогнозирования и мониторинга урогинекологических заболеваний.

Результаты

Результаты. ИИ активно используется для анализа электронных медицинских записей, интерпретации уродинамических тестов, сегментации и оценки изображений при ультразвуковых и МРТ-исследованиях, что повышает точность диагностики пролапса тазовых органов и недержания мочи. В хирургической практике технологии компьютерного зрения и дополненной реальности улучшают точность и безопасность вмешательств. Прогностические алгоритмы позволяют оценивать риск осложнений и рецидивов после операций, а телемедицинские решения и носимые устройства на основе ИИ обеспечивают непрерывный мониторинг состояния пациенток. Несмотря на высокий потенциал, большинство моделей требует дополнительной клинической валидации и стандартизации.

Заключение

Заключение. Применение ИИ в урогинекологии способствует повышению качества диагностики и лечения, развитию персонализированной медицины и улучшению клинических исходов. Для широкого внедрения технологий необходимы многоцентровые исследования, совершенствование алгоритмов и разработка этических и правовых норм использования ИИ в медицинской практике.

Introduction

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

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

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

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

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.

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The authors declare that there are no conflicts of interest present.