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Bespalova O.N.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Kogan I.Yu.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Zagainova V.A.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Shengelia M.O.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Zhernakova T.S.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Pachulya O.V.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Komarova E.M.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Lesik E.A.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Tapil’skaya N.I.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Artificial intelligent systems in the development of assisted reproductive technologies
Journal: Russian Bulletin of Obstetrician-Gynecologist. 2024;24(2): 19‑29
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To cite this article:
Bespalova ON, Kogan IYu, Zagainova VA, et al. . Artificial intelligent systems in the development of assisted reproductive technologies. Russian Bulletin of Obstetrician-Gynecologist.
2024;24(2):19‑29. (In Russ.)
https://doi.org/10.17116/rosakush20242402119
In the conditions of rapid development of computer technologies, the field of application of artificial intelligence (AI) systems is continuously expanding. During the last ten years AI programs have been actively developed and integrated into various spheres of healthcare with increasing number and complexity of the tasks they solve. Due to the ability to analyze a large set of data and high performance, AI is a promising direction in improving the accuracy and speed of diagnosis, the choice of treatment tactics and its objectification, and the possibility of individual prognosis. The programs of assisted reproductive technologies (ART) represent a sequence of stages, the effectiveness of each of which is influenced by a combination of many factors. In this regard, the application of AI systems in overcoming infertility, described for various aspects of treatment, including individual selection of stimulation schemes and monitoring of ovarian response, selection of gametes, embryos and their cryopreservation, non-invasive diagnosis of the genetic status of the embryo, and prognosis of the effectiveness of ART cycles, is relevant. This literature review was prepared on the basis of the analysis of PubMed, MedLine, eLibrary databases publications for the period 1972—2022 on the keywords Artificial Intelligence, Machine Learning in the field of reproductive medicine and embryology, and describes the main AI methods used at all stages of ART programs.
AI technologies are a promising direction for improving the quality of medical care in infertility, transition to personalized medicine and increasing the effectiveness of ART programs. The development of AI systems requires the participation of a medical specialist in the selection and preparation of data, determination of algorithm tasks, its approbation and implementation in clinical practice. It should be noted that AI systems can also be applied in the field of medical research. However, before AI algorithms are integrated, large-scale randomized controlled trials and their standardization are required, which involves solving a number of ethical, legislative and organizational issues.
Keywords:
Authors:
Bespalova O.N.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Kogan I.Yu.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Zagainova V.A.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Shengelia M.O.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Zhernakova T.S.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Pachulya O.V.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Komarova E.M.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Lesik E.A.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Tapil’skaya N.I.
D.O. Ott Research Institute of Obstetrics, Gynecology and Reproduction
Received:
22.12.2023
Accepted:
24.12.2023
List of references:
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