Backpropagation Neural Network Algorithm-Based Color Doppler Ultrasound Detection of Gestational Diabetes Mellitus and Perinatal Outcomes | Zendy

Xiaoqing Zhang | Zendy; Yinsu Lou | Zendy; Sunhao Hu | Zendy; Dan Zhu | Zendy

Open Access

Backpropagation Neural Network Algorithm-Based Color Doppler Ultrasound Detection of Gestational Diabetes Mellitus and Perinatal Outcomes

Author(s) -

Xiaoqing Zhang,

Yinsu Lou,

Sunhao Hu,

Dan Zhu

Publication year - 2021

Publication title -

scientific programming

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.269

H-Index - 36

eISSN - 1875-919X

pISSN - 1058-9244

DOI - 10.1155/2021/4258360

Subject(s) - gestational diabetes , algorithm , backpropagation , medicine , gestational age , diabetes mellitus , fetus , pregnancy , obstetrics , gestation , machine learning , artificial neural network , endocrinology , mathematics , computer science , biology , genetics

In this work, the related risk factors and perinatal outcomes of pregnant women with gestational diabetes mellitus (GDM) were analyzed based on color Doppler ultrasound (CDU) diagnosis. Backpropagation (BP) algorithm-based CDU imaging algorithm (BPC) was constructed in this study and applied in CDU images of 80 pregnant women with GDM. Besides, amplitude and phase estimation (APES) and low-complexity adaptive beam (LCA) algorithms were introduced for comparison with BPC in turn. It was found that Dice similarity coefficient (96.44%), sensitivity (95.45%), and specificity (91.56%) of BPC were greater than those of APES (83.97%, 85.84%, 78.45%) and LCA (84.74%, 86.29%, 82.35%), while its running time (6.44 ± 1.39 s) was shorter than that of APES (11.87 ± 2.41 s) and LCA (13.76 ± 1.54 s) ( P < 0.05 ). Pregnant women in the experimental group (group B) were older than those in the control group (group A) ( P < 0.05 ). The pulsatility index (PI) and renal artery resistance index (RI) of fetuses in group B (0.95 ± 0.15) were higher than those of group A (0.57 ± 0.24) ( P < 0.05 ). In addition, pregnancy age, family history of hypertension, and abortion history were positively correlated with GDM ( P < 0.05 ). In conclusion, BPC could not only improve diagnosis accuracy in fetuses’ CDU images but also shorten calculation time. Pregnancy age, family history of hypertension, and abortion history were the related risk factors for GDM in pregnant women.

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