DOI QR코드

DOI QR Code

Decision Support System Regarding the Possibility of Using the Reproductive Technologies Taking into Account Civil Law

  • Hnatchuk, Yelyzaveta (Department of Computer Engineering & Information Systems, Khmelnytskyi National University) ;
  • Hovorushchenko, Tetiana (Department of Computer Engineering & Information Systems, Khmelnytskyi National University) ;
  • Medzatyi, Dmytro (Department of Computer Engineering & Information Systems, Khmelnytskyi National University)
  • 투고 : 2022.07.05
  • 발행 : 2022.07.30

초록

The review of known methods and decision support systems regarding the possibility of using the reproductive technologies showed that currently there are no methods and decision support systems regarding the possibility of using reproductive technologies taking into account civil law. Although the analyzed methods and systems have great potential for use in different contexts, these methods and systems do not take into account the civil law requirements of any country. The paper has developed a decision support system regarding the possibility of using the reproductive technologies taking into account civil law, which automatically and free of charge determines the possibility/impossibility of surrogate motherhood or in vitro fertilization. If it is determined that surrogate motherhood or in vitro fertilization is impossible, the sufficiency of the information in the analyzed contract is evaluated, and the reasons for the impossibility of surrogate motherhood or in vitro fertilization are presented to the user.

키워드

참고문헌

  1. Herts, A.: The Peculiarities of Civil-Legal Regulation of Transplantation in Ukraine and Europe. Baltic Journal of European Studies 8(1), 33-48 (2018). https://doi.org/10.1515/bjes-2018-0003
  2. Order of the Ministry of Health "On Approval of the Procedure for the Use of Assisted Reproductive Technologies in Ukraine No. 787 of 09.09.2013". Official Journal of Ukraine 82, 446 (2013).
  3. Holovashchuk, A.: Auxiliary reproductive technologies as a way to exercise the right to maternity. In: International Scientific and Practical Conference "Rule of law, legality and human rights", p. 32 (2012).
  4. Cresswell, K., Majeed, A., Bates, D., Sheikh, A.: Computerised decision support systems for healthcare professionals: An interpretative review. The Journal of Innovation in Health Informatics 20(2), 115-128 (2012). https://doi.org/10.14236/jhi.v20i2.32
  5. Adams, C., Allen, J., Flack, F.: Data custodians and the decision-making process: releasing data for research. Journal of Law and Medicine 26(2), 433-453 (2018).
  6. Mitchell, C., Ploem, C.: Legal challenges for the implementation of advanced clinical digital decision support systems in Europe. Journal of Clinical and Translational Research 3, 424-430 (2018).
  7. Grytsenko, O., Pukach, P., Suberlyak, O., Shakhovska, N., Karovic, V.: Usage of mathematical modeling and optimization in development of hydrogel medical dressings production. Electronic (Switzerland) 10(5), 1-10 (2021).
  8. Agate, S., Curran, M.: Opportunity for legal innovation in healthcare technology. URL: https://www.lawpracticetoday.org/article/legal-innovation-healthcare-technology.
  9. Lebedev, G., Shakhova, M., Kholin, A., Malyarenko, O., Bondarenko, V., Zykov, S.: Application of a prospective assisted reproductive technologies register for calculating the probability of pregnancy. Procedia Computer Science 126, 1237-1242 (2018). https://doi.org/10.1016/j.procs.2018.08.065
  10. Cao, Q., Liao, S., Meng, X., Ye, H., Yan, Z., Wang, P.: Identification of Viable Embryos Using Deep Learning for Medical Image. In: The 2018 5th International Conference on Bioinformatics Research and Applications, pp. 69-72 (2018).
  11. Kothandaraman, R., Andavar, S., Raj, R.: A Hybrid Feature Ranking Algorithm for Assisted Reproductive Technology Outcome Prediction. Brazilian Archives of Biology and Technology 65, article number e22210605 (2022).
  12. Kothandaraman, R., Andavar, S., Raj, R.: Dynamic Model for Assisted Reproductive Technology Outcome Prediction. Brazilian Archives of Biology and Technology 64, article number e21200758 (2021).
  13. Figueira, J., Almeida-Dias, J., Matias, S., Roy, B., Carvalho, M., Plancha, C.: ELECTRE TRI-C, a multiple criteria decision aiding sorting model applied to assisted reproduction. International Journal of Medical Informatics 80(4), 262-273 (2011). https://doi.org/10.1016/j.ijmedinf.2010.12.001
  14. Letterie, G., Mac Donald, A.: Artificial intelligence in in vitro fertilization: a computer decision support system for day-to-day management of ovarian stimulation during in vitro fertilization. Fertility and Sterility 114(5), 1026-1031 (2020). https://doi.org/10.1016/j.fertnstert.2020.06.006
  15. Hariton, E., Chi, E., Chi, G., Morris, J., Braatz, J., Rajpurkar, P., Rosen, M.: A machine learning algorithm can optimize the day of trigger to improve in vitro fertilization outcomes. Fertility and Sterility 116(5), 1227-1235 (2021). https://doi.org/10.1016/j.fertnstert.2021.06.018
  16. Letterie, G.: Three ways of knowing: the integration of clinical expertise, evidence-based medicine, and artificial intelligence in assisted reproductive technologies. Journal of Assisted Reproduction and Genetics 38(7), 1617-1625 (2021). https://doi.org/10.1007/s10815-021-02159-4
  17. Chang, V., Heutte, L., Petitjean, C., Hartel, S., Hitschfeld, N.: Automatic classification of human sperm head morphology. Computers in Biology and Medicine 84, 205-216 (2017). https://doi.org/10.1016/j.compbiomed.2017.03.029
  18. Hovorushchenko, T., Herts, A., Hnatchuk, Ye.: Concept of Intelligent Decision Support System in the Legal Regulation of the Surrogate Motherhood. CEUR-WS 2488, 57-68 (2019).
  19. Hovorushchenko, T., Boyarchuk, A., Pavlova, O.: Ontology-Based Intelligent Agent for Semantic Parsing the Software Requirements Specifications. International Journal on Information Technologies and Security 2(11), 59-70 (2019).
  20. Hovorushchenko, T., Pavlova, O., Medzatyi, D.: Ontology-Based Intelligent Agent for Determination of Sufficiency of Metric Information in the Software Requirements. Advances in Intelligent Systems and Computing 1020, 447-460 (2020). https://doi.org/10.1007/978-3-030-26474-1_32