Artificial intelligence in reproductive medicine: ethical and clinical aspects
The introduction of artificial intelligence (AI) systems in medicine is one of the most important current trends in global healthcare. AI technologies can substantially update a diagnostic system and the design of new drugs and improve the quality of healthcare, by simultaneously reducing cost. Despite the obvious advantages of applying AI-based algorithms, there are a number of limitations in the implementation of these programs in healthcare. Among these problems, there is an ethical challenge in AI, as well as responsibility for programmed decision-making. Another important issue of the safe use of AI is the black box principle, when determining causal relationships between data, how the system has actually arrived at a derived conclusion cannot be determined exactly. At the moment, the major goal of AI studies should be to improve software accuracy.Drapkina Yu.S., Kalinina E.A., Makarova N.P., Milchakov K.S., Frankevich V.E.
Conclusion: The review considers the main areas of AI application, different machine learning techniques, ethical restrictions, and prospects for introducing these programs into clinical practice, including those used in assisted reproductive technologies.
Keywords
artificial intelligence
assisted reproductive technologies
reproductive medicine
machine learning
ethics
healthcare
decision support system
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Received 20.07.2022
Accepted 31.10.2022
About the Authors
Yulia S. Drapkina, PhD, Researcher, Department of IVF named after Professor B.V. Leonov, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of the Russian Federation, yu_drapkina@oparina4.ru, https://orcid.org/0000-0002-0545-1607,117997, Russia, Moscow, Academician Oparin str., 4.
Elena A. Kalinina, Dr. Med. Sci., Professor, Head of the Department of IVF named after Professor B.V. Leonov, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of the Russian Federation, e_kalinina@oparina4.ru, https://orcid.org/0000-0002-8922-2878,
117997, Russia, Moscow, Academician Oparin str., 4.
Natalya P. Makarova, Dr. Bio. Sci., Leading Researcher, Department of IVF named after Professor B.V. Leonov, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of the Russian Federation, np_makarova@oparina4.ru, https://orcid.org/0000-0003-8922-2878, 1
17997, Russia, Moscow, Academician Oparin str., 4.
Kirill S. Milchakov, PhD, Associate Professor, I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation,
https://orcid.org/0000-0003-4092-2539, 119991, Russia, Moscow, Trubetskaya str., 8-2.
Vladimir E. Frankevich, Dr. Sci. (Physical and Mathematical), Head of the Department of Systems Biology in Reproduction, Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Health of the Russian Federation, +7(495)438-07-88 (ext. 2198), v_frankevich@oparina4.ru,
117997, Russia, Moscow, Academician Oparin str., 4.
Authors’ contributions: Drapkina Yu.S. – collection and analysis of literary data, writing the article; Kalinina E.A. – editing and approval of the publication; Makarova N.P. – editing the publication; Milchakov K.S. – editing the article, analysis of the submitted literary data; Frankevich V.E. – editing of the publication, analysis of submitted literary data.
Conflicts of interest: The authors declare that there are no possible conflicts of interest.
Funding: The investigation has been conducted without attracting additional funding from third parties.
For citation: Drapkina Yu.S., Kalinina E.A., Makarova N.P., Milchakov K.S., Frankevich V.E. Artificial intelligence in reproductive medicine: ethical and clinical aspects.
Akusherstvo i Ginekologiya/Obstetrics and Gynecology. 2022; 11: 37-44 (in Russian)
https://dx.doi.org/10.18565/aig.2022.11.37-44
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