akusherstvoObstetrics, Gynecology and ReproductionАкушерство, Гинекология и Репродукция2313-73472500-3194IRBIS LLC10.17749/2313-7347/ob.gyn.rep.2026.770akusherstvo-2933Research ArticleREVIEW ARTICLEНАУЧНЫЙ ОБЗОРFundamentals of artificial intelligence application and limitations of its evidence base in assisted reproductive technologies: an analytical reviewОсновы применения искусственного интеллекта во вспомогательных репродуктивных технологиях и ограничения его доказательной базы: аналитический обзорhttps://orcid.org/0009-0002-1544-3712РомашоваА. В.RomashovaA. V.

Ромашова Анастасия Вадимовна 

443099 Самара, ул. Чапаевская, д. 89

Anastasia V. Romashova

89 Chapaevskaya Str., Samara 443099

annsssss22@mail.ruhttps://orcid.org/0009-0003-0895-1716ГукасянА. С.GukasyanA. S.

Гукасян Ани Самвеловна

350063 Краснодар, ул. имени Митрофана Седина, д. 4

Ani S. Gukasyan

4 Mitrofan Sedin Str., Krasnodar 350063

https://orcid.org/0009-0006-8712-4912АветянД. М.AvetyanD. M.

Аветян Диана Мисаковна

350063 Краснодар, ул. имени Митрофана Седина, д. 4

Diana M. Avetyan

4 Mitrofan Sedin Str., Krasnodar 350063

https://orcid.org/0009-0000-6051-5434КуноваМ. З.KunovaM. Z.

Кунова Милана Зауровна

350063 Краснодар, ул. имени Митрофана Седина, д. 4

Milana Z. Kunova

4 Mitrofan Sedin Str., Krasnodar 350063

https://orcid.org/0009-0003-5215-2276АнтонянА. А.AntonyanA. A.

Антонян Ася Арменовна

350063 Краснодар, ул. имени Митрофана Седина, д. 4

Asya A. Antonyan

4 Mitrofan Sedin Str., Krasnodar 350063

https://orcid.org/0009-0003-1584-0707МагомедоваМ. Ш.MagomedovaM. Sh.

Магомедова Марьям Шамиловна

414057 Астрахань, ул. М. Луконина, д. 12, корп. 3

Maryam Sh. Magomedova

12 bldg. 3, M. Lukonina Str., Astrakhan 414057

https://orcid.org/0009-0006-1856-9651ЗотоваА. О.ZotovaA. O.

Зотова Анна Олеговна

164170 Мирный, ул. Дзержинского, д. 3

Anna O. Zotova

3 Dzerzhinsky Str., Mirny 164170

https://orcid.org/0009-0005-7061-2322ВолчокЕ. В.VolchokE. V.

Волчок Екатерина Владимировна

344069 Ростов-на-Дону, ул. Медицинская, д. 12

Ekaterina V. Volchok

12 Meditsinskaya Str., Rostov-on-Don 344069

https://orcid.org/0009-0004-5649-1782ЕвсинаЕ. Д.EvsinaE. D.

Евсина Елена Дмитриевна

680000 Хабаровск, ул. Муравьева-Амурского, д. 35

Elena D. Evsina

35 Muravyov-Amursky Str., Khabarovsk 680000

https://orcid.org/0009-0002-0142-4430ИбрагимоваЗ. Р.IbragimovaZ. R.

Ибрагимова Залина Русланбековна

117513 Москва, ул. Островитянова, д. 1

Zalina R. Ibragimova

1 Ostrovityanova Str., Moscow 117513

https://orcid.org/0009-0000-2421-5696БороваФ. Р.BorovaF. R.

Борова Фатима Рашидовна

386001 Магас, проспект И.Б. Зязикова, д. 7

Fatima R. Borova

7 I.B. Zyazikova Avenue, Magas 386001

https://orcid.org/0009-0002-6349-2703АбдрашитоваС. Р.AbdrashitovaS. R.

Абдрашитова Сабина Робертовна, независимый исследователь

Sabina R. Abdrashitova, Independent Researcher

https://orcid.org/0009-0006-8690-0262ХуртинаВ. С.KhurtinaV. S.

Хуртина Виктория Сергеевна

420103 Казань, ул. Маршала Чуйкова, д. 54

Victoria S. Khurtina

54 Marshal Chuikov Str., Kazan 420103

ФГБОУ ВО «Самарский государственный медицинский университет» Министерства здравоохранения Российской ФедерацииРоссияSamara State Medical University, Ministry of Health of the Russian FederationRussian FederationФГБОУ ВО «Кубанский государственный медицинский университет» Министерства здравоохранения Российской ФедерацииРоссияKuban State Medical University, Ministry of Health of the Russian FederationRussian FederationГБУЗ Астраханской области «Городская поликлиника № 1»РоссияAstrakhan Region City Polyclinic No. 1Russian FederationГБУЗ Архангельской области «Мирнинская центральная городская больница»РоссияArkhangelsk Region Mirny Central City HospitalRussian FederationГБУЗ Ростовской области «Детская городская поликлиника № 18»РоссияRostov Region Children's City Polyclinic No. 18Russian FederationФГБОУ ВО «Дальневосточный государственный медицинский университет» Министерства здравоохранения Российской ФедерацииРоссияFar Eastern State Medical University, Ministry of Health of the Russian FederationRussian FederationФГАОУ ВО «Российский национальный исследовательский медицинский университет имени Н.И. Пирогова» Министерства здравоохранения Российской ФедерацииРоссияPirogov Russian National Research Medical University, Ministry of Health of the Russian FederationRussian FederationФГБОУ ВО «Ингушский государственный университет» Министерства здравоохранения Российской ФедерацииРоссияIngush State University, Ministry of Health of the Russian FederationRussian FederationГородская клиническая больница № 7 имени М. Н. СадыковаРоссияSadykov City Clinical Hospital No. 7Russian Federation20261409202600Online First2933Copyright © Romashova A.V., Gukasyan A.S., Avetyan D.M., Kunova M.Z., Antonyan A.A., Magomedova M.S., Zotova A.O., Volchok E.V., Evsina E.D., Ibragimova Z.R., Borova F.R., Abdrashitova S.R., Khurtina V.S., 20262026Ромашова А.В., Гукасян А.С., Аветян Д.М., Кунова М.З., Антонян А.А., Магомедова М.Ш., Зотова А.О., Волчок Е.В., Евсина Е.Д., Ибрагимова З.Р., Борова Ф.Р., Абдрашитова С.Р., Хуртина В.С.Romashova A.V., Gukasyan A.S., Avetyan D.M., Kunova M.Z., Antonyan A.A., Magomedova M.S., Zotova A.O., Volchok E.V., Evsina E.D., Ibragimova Z.R., Borova F.R., Abdrashitova S.R., Khurtina V.S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.gynecology.su/jour/article/view/2933Introduction

Introduction. The development of artificial intelligence (AI) and machine learning methods opens up new opportunities for optimizing clinical and laboratory stages of assisted reproductive technology (ART) programs.

Aim

Aim: to evaluate the current level of efficiency, methodological quality, and implementation prospects of AI algorithms in the clinical and laboratory stages of ART programs.

Materials and Methods

Materials and Methods. A narrative literature review was conducted using PubMed/MEDLINE, eLibrary, and ScienceDirect databases covering the years 2016–2024 (additionally including fundamental 1996–2015 studies). The search was carried out by using Boolean operators: ("artificial intelligence" OR "machine learning" OR "deep learning") AND ("IVF" OR "assisted reproductive technology" OR "embryo selection"). A total of 60 publications containing verifiable quantitative algorithm performance metrics were included in the final analysis.

Results

Results. AI use shows high accuracy in blastocyst segmentation and quality assessment (AUC = 0.86–0.91), as well as in predicting controlled ovarian hyperstimulation outcomes. However, most analyzed models are limited by single-center training datasets and a lack of external validation.

Conclusion

Conclusion. AI algorithms demonstrate high potential as decision support systems, but widespread implementation in ART practice requires prospective multicenter randomized controlled trials.

Введение

Введение. Развитие методов искусственного интеллекта (ИИ) и машинного обучения открывает новые возможности для оптимизации клинико-лабораторных этапов программ вспомогательных репродуктивных технологий (ВРТ).

Цель

Цель: оценить современный уровень эффективности, методологическое качество и перспективы внедрения алгоритмов ИИ в клинико-лабораторные этапы программ ВРТ.

Материалы и методы

Материалы и методы. Проведен нарративный обзор литературы по базам данных PubMed/MEDLINE, eLibrary и ScienceDirect за период 2016–2024 гг. (с дополнительным включением фундаментальных работ 1996–2015 гг.). Поиск осуществлялся по запросам с использованием булевых операторов: ("artificial intelligence" OR "machine learning" OR "deep learning") AND ("IVF" OR "assisted reproductive technology" OR "embryo selection"). В финальный анализ включено 60 публикаций, содержащих верифицируемые количественные метрики эффективности алгоритмов.

Результаты

Результаты. Использование ИИ показывает высокую точность в задачах сегментации и оценки качества бластоцист (AUC = 0,86–0,91), а также в прогнозировании контролируемой суперовуляции. Однако большинство проанализированных моделей ограничены моноцентровым характером обучающих выборок и отсутствием внешней валидации.

Заключение

Заключение. Алгоритмы ИИ демонстрируют высокий потенциал в качестве систем поддержки принятия решений, однако для их широкомасштабного внедрения в практику ВРТ требуется проведение проспективных многоцентровых рандомизированных контролируемых исследований.

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