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Artificial Intelligence in Health AI in embryo selection for ART

into clinical practices can enhance treatment outcomes. Availability of data
Furthermore, it is essential to implement individualized
treatment plans based on patient-specific information, All data, including the search strategy, extracted data, and
streamline laboratory procedures through automation, supplementary materials, are available on request from the
and establish strong ethical guidelines to enhance ART corresponding author.
effectiveness and maintain public trust in ART. Future References
research should focus on developing AI algorithms to
address challenges such as algorithmic bias and the 1. Cox CM, Thoma ME, Tchangalova N, et al. Infertility
need for extensive clinical validation, incorporating prevalence and the methods of estimation from 1990 to
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AI into clinical practice necessitates close collaboration
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Acknowledgments doi: 10.18502/ijrm.v20i1.10407
3. Abdullah KAL, Atazhanova T, Chavez-Badiola A, Shivhare SB.
We would like to express our deepest gratitude to all those Automation in ART: Paving the way for the future of infertility
who have contributed to the success of this research. treatment. Reprod Sci. 2023;30(4):1006-1016.
Our sincere thanks go to the esteemed faculty members doi: 10.1007/s43032-022-00941-y
of the Department of Mechatronics Engineering, whose
invaluable guidance in selecting the research topic and 4. Raef B, Ferdousi R. A review of machine learning approaches
unwavering support throughout the research process were in assisted reproductive technologies. Acta Inform Med.
instrumental in shaping this work. We also wish to extend 2019;27(3):205-211.
our heartfelt appreciation to everyone who has provided doi: 10.5455/aim.2019.27.205-211
support and assistance at every stage of this journey, 5. Wang R, Pan W, Jin L, et al. Artificial intelligence in reproductive
ensuring that challenges were met with solutions. Finally, medicine. Reproduction. 2019;158(4):R139-R154.
our most profound thanks go to our families and friends,
whose constant encouragement, love, and understanding doi: 10.1530/REP-18-0523
provided the strength and inspiration to complete this 6. Sunde A, Balaban B. The assisted reproductive technology
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Funding doi: 10.1016/j.fertnstert.2013.06.032
None. 7. Chu KY, Nassau DE, Arora H, Lokeshwar SD,
Madhusoodanan V, Ramasamy R. Artificial intelligence in
Conflict of interest reproductive urology. Curr Urol Rep. 2019;20(9):52.
The authors declare no conflicts of interest. doi: 10.1007/s11934-019-0914-4
Author contributions 8. Omur AD. Artificial intelligence in gamete cell selection and
microbiologic analysis. J Clin Vet Res. 2022;2(2):1-7.
Conceptualization: Asim Moin Saad
Visualization: Md. Abul Basar Roky, Anonno Singha Ray doi: 10.54289/JCVR2200107
Writing – original draft: Md. Abul Basar Roky 9. Afnan MAM, Rudin C, Conitzer V, et al. Ethical
Writing – review & editing: Asim Moin Saad, Anonno Implementation of Artificial Intelligence to Select Embryos
Singha Ray in in Vitro Fertilization. In: Proceedings of the 2021 AAAI/
Ethics approval and consent to participate ACM Conference on AI, Ethics, and Society. ACM; 2021.
p. 316-326.
Not applicable. doi: 10.1145/3461702.3462589

Consent for publication 10. Meseguer M, Kruhne U, Laursen S. Full in vitro fertilization
laboratory mechanization: Toward robotic assisted
Not applicable. reproduction? Fertil Steril. 2012;97(6):1277-1286.

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