Research on total time prediction method of MRI examination based on BP neural network / 医疗卫生装备

ABSTRACT

Objective To propose a total time prediction method of MRI examination based on BP neural network.Methods The clinical data of MRI equipment in some tertiary grade A hospital was mined deeply.Totally 63 examination sites and 26 examination methods were combined into several examination sequences,and the examination sequence vector and total examination time were used as the input and output of BP neural network,respectively,so as to construct a BP neural network model.The BP neural network model established was compared with the ridge regression model and Lasso regression model with the mean absolute error(MAE)as the evaluation index when used for predicting MRI examinations.Results The BP neural network model behaved better than the ridge regression model and Lasso regression model with the predicted value close to the measured value and MAE being 53.14 s.Conclusion The proposed method accurately predicts the total MRI examination time and can assist hospital staff in scheduling patient examinations.[Chinese Medical Equipment Journal,2023,44(10):13-16]