Page 17 - GTM-2-2

Global Translational Medicine Clinical algorithms in ART

endometriosis diagnostic delays on healthcare resource trigger during ovarian stimulation. Fertil Steril, 118: 101–108.
utilization and costs. Adv Ther, 37: 1087–1099.
https://doi.org/10.1016/j.fertnstert.2022.04.003
https://doi.org/10.1007/s12325-019-01215-x
31. Esteves SC, Yarali H, Ubaldi FM, et al., 2020, Validation of
21. Chapron C, Lafay-Pillet MC, Santulli P, et al., 2022, A new ART calculator for predicting the number of metaphase II
validated screening method for endometriosis diagnosis oocytes required for obtaining at least one euploid blastocyst
based on patient questionnaires. EClinicalMedicine, for transfer in couples undergoing in vitro fertilization/
44: 101263. intracytoplasmic sperm injection. Front Endocrinol
https://doi.org/10.1016/j.eclinm.2021.101263 (Lausanne), 10: 917.
22. Bailleul A, Niro J, Du Cheyron J, et al., 2021, Infertility https://doi.org/10.3389/fendo.2019.00917
management according to the Endometriosis Fertility Index 32. Arkes HR, Aberegg SK, Arpin KA, 2022, Analysis of
in patients operated for endometriosis: What is the optimal physicians’ probability estimates of a medical outcome based
time frame? PLoS One, 16: e0251372. on a sequence of events. JAMA Netw Open, 5: e2218804.
https://doi.org/10.1371/journal.pone.0251372 https://doi.org/10.1001/jamanetworkopen.2022.18804
23. Barnhart K, Dunsmoor-Su R, Coutifaris C, 2002, Effect 33. Ata B, Kalafat E, Somigliana E, 2021, A new definition of
of endometriosis on in vitro fertilization. Fertil Steril, recurrent implantation failure on the basis of anticipated
77: 1148–1155. blastocyst aneuploidy rates across female age. Fertil Steril,
https://doi.org/10.1016/s0015-0282(02)03112-6 116: 1320–1327.
24. Cakmak H, Taylor HS, 2011, Implantation failure: Molecular https://doi.org/10.1016/j.fertnstert.2021.06.045
mechanisms and clinical treatment. Hum Reprod Update, 34. Malhotra N, Malhotra J, Malhotra N, et al., 2010, Endometrial
17: 242–253. receptivity and scoring for prediction of implantation and
https://doi.org/10.1093/humupd/dmq037 newer markers. Donald Sch J Ultrasound Obstet Gynecol,
4: 439–446.
25. Boitrelle F, Shah R, Saleh R, et al., 2021, The sixth edition
of the WHO manual for human semen analysis: A critical https://doi.org/10.5005/jp-journals-10009-1164
review and SWOT analysis. Life (Basel), 11: 1368. 35. Koot YE, Saxtorph MH, Goddijn M, et al., 2019, What is
https://doi.org/10.3390/life11121368 the prognosis for a live birth after unexplained recurrent
implantation failure following IVF/ICSI? Hum Reprod,
26. Wang X, Jin L, Mao YD, et al., 2021, Evaluation of ovarian 34: 2044–2052.
reserve tests and age in the prediction of poor ovarian
response to controlled ovarian stimulation-a real-world data https://doi.org/10.1093/humrep/dez120
analysis of 89,002 patients. Front Endocrinol (Lausanne), 36. Available from: https://yourivfsuccess.com.au/estimate
12: 702061. [Last accessed on 2023 May 24].
https://doi.org/10.3389/fendo.2021.702061 37. MacLernon DJ, Raja EA, Toner JP, et al., 2022, Predicting
27. Esteves SC, Alviggi C, Humaidan P, et al., 2019, The personalized cumulative live birth following in vitro
POSEIDON criteria and Its measure of success through fertilization. Fertil Steril, 117: 326–338.
the eyes of clinicians and embryologists. Front Endocrinol https://doi.org/10.1016/j.fertnstert.2021.09.015
(Lausanne), 10: 814.
38. Available from: https://w3.abdn.ac.uk/clsm/SARTIVF [Last
https://doi.org/10.3389/fendo.2019.00814
accessed on 2023 May 24].
28. Kobanawa M, 2023, The gonadotropins starting dose 39. Liao Q, Zhang Q, Feng X, et al., 2021, Development of deep
calculator, which can be adjusted the target number learning algorithms for predicting blastocyst formation and
of oocytes and stimulation duration days to achieve quality by time-lapse monitoring. Commun Biol, 4: 415.
individualized controlled ovarian stimulation in Japanese
patients. Reprod Med Biol, 22: e12499. https://doi.org/10.1038/s42003-021-01937-1
https://doi.org/10.1002/rmb2.12499 40. Kragh MF, Karstoft H, 2021, Embryo selection with artificial
intelligence: How to evaluate and compare methods? J Assist
29. Correa N, Cerquides J, Arcos JL, et al., 2022, Supporting first
FSH dosage for ovarian stimulation with machine learning. Reprod Genet. 38: 1675–1689.
Reprod Biomed Online, 45: 1039–1045. https://doi.org/10.1007/s10815-021-02254-6
https://doi.org/10.1016/j.rbmo.2022.06.01 41. Murray KA, Gibson MI, 2022, Chemical approaches to
cryopreservation. Nat Rev Chem, 6: 579–593.
30. Fanton M, Nutting V, Solano F, et al., 2022, An interpretable
machine learning model for predicting the optimal day of https://doi.org/10.1038/s41570-022-00407-4

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