Abstract
Education is an essential axe in developing a modern, progressive and industrialized society. People must be ingrained with good quality education to be able to match up with this competitive world. In recent epoch, prenatal education by laying pre-birth prognostication of fetus in the uterus of the mother has been provoked. The grasping power of a fetus in mother's uterus is superior compared to a born child, while in the utero, baby is able hear and remember sounds which baby are able to remember even after their birth. It is also manifested that the work the mother does during the 9 months of pregnancy has a direct consequences on the evolution of child's brain. All the three aspects, i.e., health, values and creativity, go in conjunction in developing the child's mind. All the skills set, values and qualities which are acquired during pregnancy from the mother can be used to anticipate which education stream the child would be likely suitable to opt for in future. This prediction can be achieved with the help of different prediction algorithm of machine learning.
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References
Kleindorfer, S., Robertson, J.: Learning before birth. Australasian Science 34(9), 27–32 (2013)
University of Cambridge: Mother’s attitude towards baby during pregnancy may have implications for child’s development (2018)
Bhamani, S.: Educating Before Birth via Talking to the Baby in the Womb. J. Educ. Educ. Dev. 4, 368. https://doi.org/10.22555/joeed.v4i2.1736
Alvarez-Buylla, A., et al.: Birth of projection neurons in the higher vocal center of the canary forebrain before, during, and after song learning. Proc. Natl. Acad. Sci. U.S.A. 85(22), 8722–8726 (1988). https://doi.org/10.1073/pnas.85.22.8722
Reissland, N. et al.: Do facial expressions develop before birth? PloS One 6(8), e24081. https://doi.org/10.1371/journal.pone.0024081(2011)
Tastan, A., Hardalac, N., Kavak, S.B., Hardalaç, F.: Detection of fetal reactions to maternal voice using doppler ultrasound signals. In: 2018 International Conference on Artificial Intelligence and Data Processing, 2(5), 99–110 (2016)
Standford Children Care—“Risks of Pregnancy Over Age 30”
Svensson, J. et al.: Effective antenatal education: strategies recommended by expectant and new parents. J. Perinatal Educ. 17(4), 33–42 (2008). https://doi.org/10.1624/105812408X364152
Angra, S., Ahuja, S.: Machine learning and its applications: a review. In: 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), Chirala, pp. 57–60 (2017). https://doi.org/10.1109/ICBDACI.2017.8070809
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Mehta, H.N., Aher, J.G. (2021). Pre-birth Prognostication of Education and Learning of a Fetus While in the Uterus of the Mother Using Machine Learning. In: Gunjan, V.K., Suganthan, P.N., Haase, J., Kumar, A. (eds) Cybernetics, Cognition and Machine Learning Applications. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-6691-6_4
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DOI: https://doi.org/10.1007/978-981-33-6691-6_4
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