Method for predicting risk of spontaneous premature birth in pregnant woman using artificial intelligence, involves using direct propagation artificial neural network comprising input layer, three hidden layer and output layer, and dividing output values into two groups
	MATIUSHONOK E N; KUZMIN A I
	2023-05-23
专利权人	UNIV SMOLENSK STATE MEDICAL (UYSM-Non-standard)
申请日期	2023-05-23
专利号	RU2023113399-A
成果简介	NOVELTY - The method involves performing analysis of clinical and anamnestic, laboratory and instrumental research results and the results of tests conducted using the SAN method. The type of psychological component of the gestational dominant is determined. The maternal age, marital status, maternal smoking, paternal smoking, paternal alcohol abuse, history of number of missed pregnancies, miscarriages, sexually transmitted infections in the mother, and isthmic-cervical insufficiency in the mother's current pregnancy are determined. The direct propagation artificial neural network comprising input layer, three hidden layer and output layer, is used. The output values are divided into two groups by artificial neural network. The patients with an output value greater than or equal to 0.7 are classified as having a high risk of premature birth in a given pregnancy. The patients with output value less than 0.7, are classified as having no risk of premature birth in given pregnancy. USE - Method for predicting risk of spontaneous premature birth in pregnant woman using artificial intelligence.
IPC 分类号	A61B-005/107 ; A61B-005/16 ; A61B-008/00 ; G01N-033/48 ; G06N-003/04
国家	俄罗斯
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/21804
专题	中国科学院新疆生态与地理研究所
作者单位	UNIV SMOLENSK STATE MEDICAL (UYSM-Non-standard)
推荐引用方式 GB/T 7714	MATIUSHONOK E N,KUZMIN A I. Method for predicting risk of spontaneous premature birth in pregnant woman using artificial intelligence, involves using direct propagation artificial neural network comprising input layer, three hidden layer and output layer, and dividing output values into two groups. RU2023113399-A[P]. 2023.

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