Comparison of artificial neural network and logistic regression model for factors affecting birth weight
نویسندگان
چکیده
منابع مشابه
Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model
Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS.Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE fo...
متن کاملComparison of Artificial Neural Network and Multiple Regression Analysis for Prediction of Fat Tail Weight of Sheep
A comparative study of artificial neural network (ANN) and multiple regression is made to predict the fat tail weight of Balouchi sheep from birth, weaning and finishing weights. A multilayer feed forward network with back propagation of error learning mechanism was used to predict the sheep body weight. The data (69 records) were randomly divided into two subsets. The first subset is the train...
متن کاملComparison of Artificial Neural Network and Regression Models for Prediction of Body Weight in Raini Cashmere Goat
The artificial neural networks (ANN) are the learning algorithms and mathematical models, which mimic the information processing ability of human brain and can be used to non linear and complex data. The aim of this study was to compare artificial neural network and regression models for prediction of body weight in Raini Cashmere goat. The data of 1389 goats for body weight, height at withers ...
متن کاملComparison of Prediction Model for Cardiovascular Autonomic Dysfunction Using Artificial Neural Network and Logistic Regression Analysis
BACKGROUND This study aimed to develop the artificial neural network (ANN) and multivariable logistic regression (LR) analyses for prediction modeling of cardiovascular autonomic (CA) dysfunction in the general population, and compare the prediction models using the two approaches. METHODS AND MATERIALS We analyzed a previous dataset based on a Chinese population sample consisting of 2,092 in...
متن کاملThe Comparison of Credit Risk between Artificial Neural Network and Logistic Regression Models in Tose-Taavon Bank in Guilan
One of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. The considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. Accordingly...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SN Applied Sciences
سال: 2019
ISSN: 2523-3963,2523-3971
DOI: 10.1007/s42452-019-0391-x