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The Journal "Obstetrics and Gynecology"Journal HistoryAims and ScopePolicies on Conflict of Interest, Human and Animal Rights, and Informed ConsentEditorial ProcessData sharing statementAdvertising PolicyThe Process for Handling Cases Requiring Corrections, Retractions, and Editorial Expressions of ConcernEditorial BoardEditorial CounsilInformation for ProfessionalsNewsContacts
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For authors
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Obstetrics and Gynegology2026№8

The use of artificial intelligence in the diagnosis and treatment of hormonal disorders in women of reproductive age

DOI
https://dx.doi.org/10.18565/aig.2026.96

Sheshukova N.A., Shatilina A.Yu., Antoshina K.R., Sukhanova M.A., Khachaturov A.A., Titkova E.R., Levakov S.A.

I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia (Sechenov University), Moscow, Russia

Hormonal disorders in women of reproductive age, including polycystic ovary syndrome, hyperandrogenism, thyroid dysfunction and hyperprolactinemia, are characterized by clinical heterogeneity and considerable variability in laboratory parameters, which significantly complicate timely diagnosis and the choice of optimal therapy. This review analyzes the latest findings on the use of artificial intelligence (AI) and machine learning methods to study laboratory, clinical, and imaging data, with the aim of improving diagnostic accuracy and personalized treatment strategies. The use of AI makes it possible to integrate diverse sources of information, namely hormone profiles, medical imaging data, clinical and medical history characteristics as well as their changes over time, and to identify complex non-linear relationships that cannot be detected using traditional analytical methods. The implementation of AI as a tool to support clinical decision-making is of particular importance. It has been shown that the use of AI helps to assess the risk of developing diseases at the primary screening stage, improve the accuracy of differential diagnosis and predict response to treatment; this, in turn, can facilitate and accelerate the clinician’s work, as well as reduce the likelihood of diagnostic errors.    
Conclusion. AI methods hold considerable potential for improving the diagnosis and management of conditions such as polycystic ovary syndrome, hyperandrogenism, thyroid dysfunction and hyperprolactinemia. However, the use of AI in clinical practice is limited by small sample sizes, insufficient external validation of models, issues regarding the interpretability of algorithms and data protection concerns. There is a need to standardize approaches and establish representative databases in order to improve accuracy and ensure the successful integration of AI into routine medical practice.  

Authors’ contributions. Sheshukova N.A., Levakov S.A. – developing the concept of the article; Shatilina A.Yu., Antoshina K.R., Sukhanova M.A., Khachaturov A.A., Titkova E.R., Sheshukova N.A. – collecting and processing the material, writing the text; Sheshukova N.A. – editing the text.
Conflicts of interest. Authors declare lack of the possible conflicts of interests.
Funding. The study was conducted without sponsorship.
Generative Artificial Intelligence. Whilst preparing the manuscript, the authors used artificial intelligence tools 
(https://chatgpt.com/) to edit the style and improve the logical coherence of the text. The authors retain full responsibility for the final version, the interpretation of the results and the content.
For citation: Sheshukova N.A., Shatilina A.Yu., Antoshina K.R., Sukhanova M.A., Khachaturov A.A., 
Titkova E.R., Levakov S.A. The use of artificial intelligence in the diagnosis and 
treatment of hormonal disorders in women of reproductive age.
 Akusherstvo i Ginekologiya/Obstetrics and Gynecology. 2026; (8): 55-62 (in Russian)
https://dx.doi.org/10.18565/aig.2026.96

Keywords

artificial intelligence
machine learning
polycystic ovary syndrome
hyperandrogenism
hypothyroidism
hyperthyroidism
hyperprolactinemia
personalized medicine
Full text (in Russian)

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Received 20.03.2026

Accepted 17.07.2026

About the Authors

Nataliya A. Sheshukova, Dr. Med. Sci., Professor at the Department of Obstetrics and Gynecology, N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov First Moscow State Medical University, Ministry of Health of Russia (Sechenov University), 119991, Russia, Moscow, Trubetskaya str., 8, build. 2, sheshukova_n_a@staff.sechenov.ru,
https://orcid.org/0000-0002-8757-0131
Anastasia Y. Shatilina, student, N.V. Sklifosovsky Institute of Clinical Medicine, Educational Track: Research, I.M. Sechenov First Moscow State Medical University,
Ministry of Health of Russia (Sechenov University), 119991, Russia, Moscow, Trubetskaya str., 8, build. 2, shatilina1110@gmail.com, https://orcid.org/0009-0006-6018-4667
Kamilla R. Antoshina, student, N.V. Sklifosovsky Institute of Clinical Medicine, Educational Track: Research, I.M. Sechenov First Moscow State Medical University,
Ministry of Health of Russia (Sechenov University), 119991, Russia, Moscow, Trubetskaya str., 8, build. 2, kam11_03@mail.ru, https://orcid.org/0000-0002-4096-0060
Maria A. Sukhanova, student, N.V. Sklifosovsky Institute of Clinical Medicine, Educational Track: Research, I.M. Sechenov First Moscow State Medical University,
Ministry of Health of Russia (Sechenov University), 119991, Russia, Moscow, Trubetskaya str., 8, build. 2, suxanovamaria@gmail.com, https://orcid.org/0009-0001-4792-4353
Artem A. Khachaturov, student, N.V. Sklifosovsky Institute of Clinical Medicine, Educational Track: Research, I.M. Sechenov First Moscow State Medical University,
Ministry of Health of Russia (Sechenov University), 119991, Russia, Moscow, Trubetskaya str., 8, build. 2, a.khachaturov-03@mail.ru, https://orcid.org/0009-0000-0711-9619
Eva R. Titkova, student, N.V. Sklifosovsky Institute of Clinical Medicine, Educational Track: Research, I.M. Sechenov First Moscow State Medical University,
Ministry of Health of Russia (Sechenov University), 119991, Russia, Moscow, Trubetskaya str., 8, build. 2, titkova.e.r@mail.ru, https://orcid.org/0009-0008-5735-5781
Sergey A. Levakov, Dr. Med. Sci., Professor, Head of the Department of Obstetrics and Gynecology, N.V. Sklifosovsky Institute of Clinical Medicine, I.M. Sechenov
First Moscow State Medical University, Ministry of Health of Russia (Sechenov University), 119991, Russia, Moscow, Trubetskaya str., 8, build. 2,
levakov_s_a@staff.sechenov.ru, https://orcid.org/0000-0002-4591-838X

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