概要
目的
建立一个预测妊娠期糖尿病新生儿出生体重的人工神经网络模型, 并评估其预测的准确性。
创新点
妊娠期糖尿病新生儿出生体重的预测十分重要, 但目前预测精度欠佳。本研究利用大样本量的临床数据, 突破传统统计学方法, 应用机器学习建立了一个基于人工神经网络的预测模型, 其预测精度较传统方法有明显提升。
方法
收集2462名妊娠期糖尿病孕妇的临床数据, 其中80%的数据用于构建一个前馈神经网络模型, 并用反向传播算法和10折交叉验证法训练和优化;剩余20%的数据用于验证最终模型的性能, 并将其与传统方法进行比较。
结论
本研究构建的人工神经网络模型对妊娠期糖尿病新生儿出生体重具有较高的预测精度, 其预测能力优于传统方法, 不足之处则在于其仍有可能会低估高出生体重。
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Acknowledgments
This work was supported by the Key Research and Development Project of Zhejiang Province (No. 2018C03010) and the Natural Science Foundation of Zhejiang Province (No. LQ20H040005), China.
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Detailed methods are provided in the electronic supplementary materials of this paper.
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Materials and methods; Table S1
Author contributions
Menglin ZHOU performed the data analysis, wrote and edited the manuscript. Jiansheng JI and Nie XIE performed the data collection. Danqing CHEN performed the study design, funding support, and process supervision. All authors have read and approved the final manuscript, and therefore, have full access to all the data in the study and take responsibility for the integrity and security of the data.
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Menglin ZHOU, Jiansheng JI, Nie XIE, and Danqing CHEN declare that they have no conflict of interest.
All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Informed consent was not obtained since de-identified retrospective data were collected and it was approved by the Institutional Ethics Committee of Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, China (No. IRB-20210136-R).
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Zhou, M., Ji, J., Xie, N. et al. Prediction of birth weight in pregnancy with gestational diabetes mellitus using an artificial neural network. J. Zhejiang Univ. Sci. B 23, 432–436 (2022). https://doi.org/10.1631/jzus.B2100753
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DOI: https://doi.org/10.1631/jzus.B2100753