, , PREDICTION OF CLINICAL NARROW PELVIS USING NEURAL NETWORK DA- TA ANALYSIS // BSU bulletin. Medicine and pharmacy. - 2022. №2. . - С. 19-23.

PREDICTION OF CLINICAL NARROW PELVIS USING NEURAL NETWORK DA- TA ANALYSIS

DOI: 10.18101/2306-1995-2022-2-19-23 UDK: 618.33-007.61

The prevalence of clinical narrow pelvis is 1.3-1.7%, which is associated with an increase in the frequency of childbirth with a large fetus, as well as the appearance of "erased" forms of anatomically narrow pelvis. Fetal-pelvic disproportion is one of the most important factors determining the frequency of intranatal fetal injuries, which deter- mines the relevance of this study. The aim of the study was to evaluate the capabilities of neural network data analysis in predicting a clinical narrow pelvis. A retrospective analy- sis of 184 birth histories for 2018-2021 was carried out on the basis of the perinatal center of the Regional Clinical Hospital. The total sample was divided into 2 study groups: group 1 icluded 135 patients who gave birth through the natural birth canal; Group 2 included 49 patients whose delivery was complicated by the development of clinically narrow pelvis. Statistically significant parameters such as oligohydramnios, macrosomia, abdominal cir- cumference, fundal height, and fetal head circumference were included in the test data- base, which formed the basis for training the multilayer perceptron. The structure of the trained neural network included 7 input neurons, one hidden layer containing 9 units, and 2 output neurons (Se=1.00, Sp=0.98, AUC=0.99 [95% CI 0.97-1.00 ], p<0.001).

clinical narrow pelvis, fetal-pelvic disproportion, intranatal period, neural net- work analysis, neural network, multilayer perceptron.