Volume 9, Issue 3 (2024)
SJMR 2024, 9(3): 171-176 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Shafti V, Azarboo A. Artificial Intelligence Model Using Endometrial Analysis as A Predictor of Assisted Reproductive Technology Success During Embryo Transfer - A Review Article. SJMR 2024; 9 (3) : 5
URL: http://saremjrm.com/article-1-313-en.html
URL: http://saremjrm.com/article-1-313-en.html
1- School of Medicine, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran
2- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
2- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
Abstract: (1364 Views)
The integration of artificial intelligence (AI) into assisted reproductive technology (ART) has emerged as a transformative approach to enhance the success rates of in vitro fertilization (IVF) and other reproductive interventions. One significant advancement in this field developing the EndoClassify model, which utilizes endometrial analysis to predict ART outcomes. This article explores the methodology, findings, and implications of using AI for assessing endometrial receptivity and improving embryo transfer success.
Article number: 5
Article Type: Systematical Review |
Subject:
Sterility
Received: 2024/11/5 | Accepted: 2024/12/15 | Published: 2025/01/18
Received: 2024/11/5 | Accepted: 2024/12/15 | Published: 2025/01/18
References
1. Turner K, Reynolds-May MF, Zitek EM, Tisdale RL, Carlisle AB, Westphal LM. Stress and anxiety scores in first and repeat IVF cycles: a pilot study. PLoS One. 2013;8(5):e63743. [DOI:10.1371/journal.pone.0063743] [PMID] []
2. Meirzon D, Jaffa AJ, Gordon Z, Elad D. A new method for analysis of non-pregnant uterine peristalsis using transvaginal ultrasound. Ultrasound Obstet Gynecol. 2011;38(2):217-24. [DOI:10.1002/uog.8950] [PMID]
3. Mathyk B, Schwartz A, DeCherney A, Ata B. A critical appraisal of studies on endometrial thickness and embryo transfer outcome. Reprod Biomed Online. 2023;47(4):103259. [DOI:10.1016/j.rbmo.2023.103259] [PMID] []
4. Reid S, Nadim B, Bignardi T, Lu C, Martins WP, Condous G. Association between three-dimensional transvaginal sonographic markers and outcome of pregnancy of unknown location: a pilot study. Ultrasound Obstet Gynecol. 2016;48(5):650-5. [DOI:10.1002/uog.15923] [PMID]
5. Liao S, Wang R, Hu C, Pan W, Pan W, Yu D, Jin L. Analysis of endometrial thickness patterns and pregnancy outcomes considering 12,991 fresh IVF cycles. BMC Med Inform Decis Mak. 2021;21(1):176. [DOI:10.1186/s12911-021-01538-2] [PMID] []
6. Zegers-Hochschild F, Adamson GD, Dyer S, Racowsky C, de Mouzon J, Sokol R, et al. The International Glossary on Infertility and Fertility Care, 2017. Hum Reprod. 2017;32(9):1786-801. [DOI:10.1093/humrep/dex234] [PMID] []
7. Macklon NS, Geraedts JP, Fauser BC. Conception to ongoing pregnancy: the 'black box' of early pregnancy loss. Hum Reprod Update. 2002;8(4):333-43. [DOI:10.1093/humupd/8.4.333] [PMID]
8. Mahutte N, Hartman M, Meng L, Lanes A, Luo ZC, Liu KE. Optimal endometrial thickness in fresh and frozen-thaw in vitro fertilization cycles: an analysis of live birth rates from 96,000 autologous embryo transfers. Fertil Steril. 2022;117(4):792-800. [DOI:10.1016/j.fertnstert.2021.12.025] [PMID]
9. Greenwald NF, Miller G, Moen E, Kong A, Kagel A, Dougherty T, et al. Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning. Nat Biotechnol. 2022;40(4):555-65. [DOI:10.1038/s41587-021-01094-0] [PMID] []
10. Yamaguchi M, Yoshihara K, Suda K, Nakaoka H, Yachida N, Ueda H, et al. Three-dimensional understanding of the morphological complexity of the human uterine endometrium. iScience. 2021;24(4):102258. [DOI:10.1016/j.isci.2021.102258] [PMID] []
11. Gardner DK, Lane M, Stevens J, Schlenker T, Schoolcraft WB. Blastocyst score affects implantation and pregnancy outcome: towards a single blastocyst transfer. Fertil Steril. 2000;73(6):1155-8. [DOI:10.1016/S0015-0282(00)00518-5] [PMID]
12. Bulletti C, Franasiak JM, Busnelli A, Sciorio R, Berrettini M, Aghajanova L, et al. Artificial Intelligence, Clinical Decision Support Algorithms, Mathematical Models, Calculators Applications in Infertility: Systematic Review and Hands-On Digital Applications. Mayo Clinic Proceedings: Digital Health. 2024;2(4):518-32. [DOI:10.1016/j.mcpdig.2024.08.007] [PMID] []
13. Asch R, Suarez J, Laugas N, Ramirez M, Alkon T. Artificial intelligence model utilizing endometrial analysis to contribute as a predictor of assisted reproductive technology success. Journal of IVF-Worldwide. 2024;2. [DOI:10.46989/001c.115893]
14. Do not use your browser's 'BACK' button.
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
