Development of a machine learning–based prediction model for clinical pregnancy of intrauterine insemination in a large Chinese population
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10815-024-03153-2.pdf
Reference43 articles.
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2. Nandi A, Raja G, White D, Tarek ET. Intrauterine insemination + controlled ovarian hyperstimulation versus in vitro fertilisation in unexplained infertility: a systematic review and meta-analysis. Arch Gynecol Obstet. 2022;305:805–24.
3. Bai F, Wang DY, Fan YJ, Qiu J, Wang L, Dai Y, et al. Assisted reproductive technology service availability, efficacy and safety in mainland China: 2016. Hum Reprod. 2020;35:446–52.
4. Kozar N, Kovač V, Reljič M. Can methods of artificial intelligence aid in optimizing patient selection in patients undergoing intrauterine inseminations? J Assist Reprod Genet. 2021;38:1665–73.
5. Garcia-Grau E, Oliveira M, Amengual MJ, Rodriguez-Sanchez E, Veraguas-Imbernon A, Costa L, et al. An algorithm to predict the lack of pregnancy after intrauterine insemination in infertile patients. J Clin Med. 2023;12:3225.
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