MANAGEMENT STRATEGIES FOR IMPLEMENTING ARTIFICIAL INTELLIGENCE IN THE CLINICAL PRACTICE OF REPRODUCTIVE CENTERS: OVERCOMING THE "IMPLEMENTATION VALLEY"

• Mamedova Guzal Bakirovna

  Author

• Goikhman Yaron Borisovich

  Author

• Adkhamova Negina Pulatovna

  Author

Artificial intelligence (AI) technologies, including machine learning and deep neural networks, are becoming a key driver of personalized medicine. In reproductive medicine, AI demonstrates high efficacy in predicting the success of in vitro fertilization (IVF), automated assessment of embryo morphology, and analysis of preimplantation genetic testing data [1, 2].

Tran D. et al. Artificial intelligence in assisted reproductive technology: a systematic review // RBMO. 2022. Vol. 44, № 2. P. 343–353.

Verbitskaya E.A., Smirnova A.A. [Digital technologies and artificial intelligence in reproductive medicine: an overview of opportunities] // Problemy reproduktsii. 2023. Vol. 29, № 1. P. 15–25. Russian.

Coiera E. The fate of medicine in the time of AI // The Lancet. 2018. Vol. 392. P. 2331–2332.

Maistrenko N.A. [Management aspects of innovation implementation in medical organizations] // Menedzher zdravookhraneniya. 2022. № 5. P. 34–42. Russian.

Shaw J. et al. Beyond the algorithm: the human and organizational factors in AI implementation for healthcare // BMJ Health & Care Informatics. 2021. Vol. 28, № 1.

Semenov V.Yu., Kalinina N.M. [Digital transformation of healthcare: economic and organizational challenges] // Finansy i biznes. 2021. Vol. 17, № 3. P. 78–95. Russian.

Greenhalgh T. et al. Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies // J Med Internet Res. 2017. Vol. 19, № 11.

Pesapane F. et al. Key challenges for implementing artificial intelligence in radiology // Insights into Imaging. 2022. Vol. 13, № 1. P. 1–10.

Gerke S. et al. Ethical and legal challenges of artificial intelligence-driven healthcare // Artificial Intelligence in Healthcare. 2020. P. 295–336.

Rousseau D.M. Evidence-based management: lessons from evidence-based medicine // Academy of Management Perspectives. 2022. Vol. 36, № 3.

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