Analysis of the relationship between fetal health prediction features with machine learning feyn qlattice regression model-Reference-Cited by-同舟云学术

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Analysis of the relationship between fetal health prediction features with machine learning feyn qlattice regression model

Published:2023 Issue: Volume: Page:
ISSN:0094-243X
Container-title:3RD INTERNATIONAL CONFERENCE OF BIO-BASED ECONOMY FOR APPLICATION AND UTILITY
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Author:

Purwono Purwono,Wirasto Anggit,Setiawan Retno Agus,Triwibowo Deni Nugroho,Zuhrufillah Irfani,Sumantri R. Bagus Bambang,Supriyatin Supriyatin

Publisher

AIP Publishing

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0120255

Reference30 articles.

1. Nelson, K.M.; Irvin-Choy, N.; Hoffman, M.K.; Gleghorn, J.P.; Day, E.S. Diseases and Conditions That Impact Maternal and Fetal Health and the Potential for Nanomedicine Therapies. Adv. Drug Deliv. Rev. 2021, 170, 425–438, doi:https://doi.org/10.1016/j.addr.2020.09.013.

2. Society for Maternal-Fetal Medicine Special Statement: Updated checklist for antepartum care of pregestational diabetes mellitus

3. Reissland, N.; R. Wood, J.E.; Lane, A. Effects of Maternal Mental Health on Fetal Visual Preference for Face-like Compared to Non-Face like Light Stimulation. Early Hum. Dev. 2020, 151, 105227, doi:https://doi.org/10.1016/j.earlhumdev.2020.105227.

4. Maternal health care wearing equipment based on fetal information monitoring

5. Electronic intrapartum fetal monitoring: a systematic review of international clinical practice guidelines

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1. New Media as a Tools to Improve Creative Thinking: A Systematic Literature Review;2023 IEEE 7th International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE);2023-11-29

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