Prediction of newborn birth weight and type of delivery based on perceptron neural network and decision tree

سال انتشار: 1402
محل انتشار: شانزدهمین سمپوزیوم بین المللی پیشرفت های علوم و تکنولوژی
کد COI اختصاصی: COMPUTER08_017
زبان مقاله: انگلیسی
تعداد مشاهده: 368

نویسندگان

PhD of Reproductive Health, Shahid Hasheminejad Hospital, Medical Sciences University Of Mashhad, Mashhad,Iran

Master of Biomedical Engineering, Clinical Research Development Unit ,Shahid Hasheminejad Hospital, Medical Sciences University Of Mashhad, Mashhad,Iran

Behrang Rezvani Kakhki

Associate Professor of Emergency medicine, Department of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

Behroz Zargarzada

PhD Student of Biomedical Engineering, Department of Biomedical Engineering, Faculty of Engineering, Islamic Azad University Of Mashhad, Mashhad, Iran

چکیده

Currently, all women with gestational diabetes, even those with no signs of fetal macrosomia, are closely monitored. This type of surveillance involves time and financial costs for both women and health services. If it is possible to use artificial intelligence network to prove which unborn babies of pregnant women are overweight, aggressive monitoring and treatment for those women whose unborn babies are not overweight will be reduced and risks will be avoided. And possible side effects are reduced and the time, resources and anxiety of mothers and health care personnel can be controlled. Therefore, this research was carried out by using perceptron neural network and decision tree and extracting a series of characteristics from pregnant mothers to predict the weight of the baby at birth and the type of delivery. The results indicate that the neural network used has an acceptable efficiency to estimate the newborn birth weight and type of delivery

کلیدواژه ها

Newborn birth weight, Type of delivery, Perceptron neural network, Decision tree

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