Predicting Neonatal Hypoglycemia Using AI Neural Networks in Infants from Mothers with Gestational Diabetes Mellitus

Zhimin Zhang; Ying Feng; Yu Zhang; Xia Li; Yanfei Li; Lulu Sun; Xianying Li; Hui Du; Jingxiao Zhang

doi:10.12659/MSM.944513

11 October 2024 : Clinical Research

Predicting Neonatal Hypoglycemia Using AI Neural Networks in Infants from Mothers with Gestational Diabetes Mellitus

Zhimin Zhang^1ABCDEFG, Ying Feng^1ABCDEF, Yu Zhang^2ABC, Xia Li^1ABC, Yanfei Li^3BCF, Lulu Sun^1BC, Xianying Li^1D, Hui Du^1AEFG, Jingxiao Zhang^1AEFG*

DOI: 10.12659/MSM.944513

Med Sci Monit 2024; 30:e944513

Authors information Article notes Copyright and License information

Introduction Material and Methods Results Discussion Conclusions References

Related articles Order reprints Share article Share by email

View HTML version

Figure 3 Comparison of the experimental data and the predicted results by the artificial neural network (ANN) for neonate blood concentration in the testing databaseThe scatter plot shows experimental values (line) vs ANN-predicted values (yellow “x”) for the lowest neonate blood concentration in the first 24 h of life. (Figure was generated using Python software, version 3.12.3, Python Software Foundation).

Back to the Article

Predicting Neonatal Hypoglycemia Using AI Neural Networks in Infants from Mothers with Gestational Diabetes Mellitus

Your Privacy