Open Access
Issue
E3S Web Conf.
Volume 491, 2024
International Conference on Environmental Development Using Computer Science (ICECS’24)
Article Number 03019
Number of page(s) 6
Section Health Development
DOI https://doi.org/10.1051/e3sconf/202449103019
Published online 21 February 2024
  1. Silver D, Huang A, Maddison CJ, Guez A, Sifre L, et al . Mastering the game of Go with deep neural networks and tree search. Nature (2016) 484–489. [CrossRef] [PubMed] [Google Scholar]
  2. Andreu-Perez J, Poon CC, Merrifield RD et al. Big data for health. IEEE Journal of Biomedical and Health Informatics 2015; 1193–1208. [CrossRef] [PubMed] [Google Scholar]
  3. Patel VL, Shortliffe EH, Stefanelli M, Szolovits P, Berthold MR, Bellazzi R, AbuHanna A. The coming of age of artificial intelligence in medicine. Artificial Intelligence in Medicine 2009; 5–17. [CrossRef] [PubMed] [Google Scholar]
  4. Siristatidis C, Vogiatzi P, Pouliakis A, Trivella M, Papantoniou N, Bettocchi S.. Predicting IVF outcome: A proposed web-based system using artificial intelligence. In Vivo 2016;507–512. [Google Scholar]
  5. HarperJMagliMCLundinKBarratt. When and how should new technology be introduced into the IVF laboratory?Hum Reprod2012 [Google Scholar]
  6. Sanchez-CalabuigMJLopez-CardonaAPFernandez-GonzalezRRamos-IbeasPFonseca BalvisNLaguna-Barraza. Potential health risks associated to icsi: insights from animal models and strategies for a safe procedure. Front Public Health. 2014(2);241 [Google Scholar]
  7. Tejera A MollaMMurielLRemohiJPellicer. Successful pregnancy and childbirth after intracytoplasmic sperm injection with calcium ionophore oocyte activation in a globozoospermic patient.FertilSteril. 2008, 90; 1202. [Google Scholar]
  8. Moher D LiberatiATetzlaffJAltmanDG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.Open Med. 2009,6(7); e1000097 [Google Scholar]
  9. Speroff L, Fritz, M The clinical gynecologic endocrinology and infertility. Lippincott Williams & Wilkins, Philadelphia 2005 7th Edition. [Google Scholar]
  10. Ruiter-Ligeti J, Agbo C, MJMG D (2017) The impact of semen processing on sperm parameters and pregnancy rates with intrauterine inseminations. Minerva Ginecol 69(3):218. [PubMed] [Google Scholar]
  11. Ghaffari F, Sadatmahalleh SJ, Akhoond MR, Yazdi PE, Zolfaghari ZJI (2015) Evaluating the effective factors in pregnancy after intrauterine insemination: a retrospective study. Int J FertilSteril 9(3):300 [Google Scholar]
  12. Pereira NJF (2019) Total motile count as predictor of live birth in intrauterine insemination cycles. FertilSteril 111(4):674. [Google Scholar]
  13. Butcher MJ, Janoo J, Broce M, Seybold DJ, Gantt P, Randall GJTJorm. (2016) Use of sperm parameters to predict clinical pregnancy with intrauterine insemination. J Reprod Med. 61(5-6):263–269 [PubMed] [Google Scholar]
  14. Stewart J, Sprivulis P, Dwivedi G. Artificial intelligence and machine learning in emergency medicine. Emergency Medicine Australasia. 2018, 870–874. [CrossRef] [PubMed] [Google Scholar]
  15. Kohli M, Prevedello LM, Filice RW, Geis JR. Implementing machine learning in radiology practice and research. American Journal of Roentgenology.2017, 754–760. [Google Scholar]
  16. Abdel Razek AAK, Alksas A, Shehata M, AbdelKhalek A, Abdel Baky K, El-Baz A, et al. Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging. Insights Imaging. 2021 Oct 21;12:152. [CrossRef] [PubMed] [Google Scholar]
  17. Ainsworth AJ, Barnard EP, Baumgarten SC, Weaver AL, Khan Z (2020) Intrauterine insemination cycles: prediction of success and thresholds for poor prognosis and futile care. Journal of assisted reproduction and genetics 37(10):2435–2442. [CrossRef] [PubMed] [Google Scholar]
  18. https://www.drhrishikeshpai.com/icsi-treatment-all-you-need-to-know/ [Google Scholar]
  19. https://www.newlifefertilityclinic.com/blog/intrauterine-insemination-iui-successrates-factor [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.