Repository of Research and Investigative Information

Repository of Research and Investigative Information

Ilam University of Medical Sciences

Forecasting Psychological Symptoms in Mild Traumatic Brain Injury: A Nonparametric Approach

Sat Oct 1 18:20:19 2022

(2019) Forecasting Psychological Symptoms in Mild Traumatic Brain Injury: A Nonparametric Approach. Iranian Journal of Psychiatry and Behavioral Sciences. p. 5. ISSN 1735-8639

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Abstract

Background: Nowadays, forecasting models based on nonparametric models have been developed in many branches of science such as mathematics and economics. However, the relatively complicated structure of these models has made them less practical in medical sciences. Objectives: In this study, we investigated the application of a nonparametric regression model to predict the psychological symptoms appearing six months after mild traumatic brain injury. We also made a comparison between the performance of nonparametric regression and artificial neural network models in predicting the psychological symptoms. Methods: In a six-month period during 2015-2017, information of 100 mild traumatic patients was included in a prospective cohort study. The data were then divided randomly into two groups of training (n = 50) and testing (n = 50) for 100 times. In the training group, the focus was on 100 artificial neural network and nonparametric regression models. However, in the testing group, a comparison was made between the values obtained using the two final models. To compare the models, the ROC curve and the accuracy rate were finally applied. Results: According to the obtained results, the nonparametric regression model showed an accuracy rate of 91.25 while the neural network model had an accuracy rate of 85.34. In the experimental set for both neural network and nonparametric regression models, the area under the ROC curve appeared to be 81.51 and 85.73 , respectively. Conclusions: The nonparametric regression model appeared to be more powerful than the neural network model in predicting psychological symptoms.

Item Type: Article
Creators:
CreatorsEmail
Nademi, A.UNSPECIFIED
Shafiei, E.UNSPECIFIED
Valizadeh, R.UNSPECIFIED
Keywords: Neural Network Statistics Nonparametric Forecasting Brain Concussion Behavioral Symptoms quantile regression variable selection prediction models Psychiatry
Divisions:
Page Range: p. 5
Journal or Publication Title: Iranian Journal of Psychiatry and Behavioral Sciences
Journal Index: ISI
Volume: 13
Number: 3
Identification Number: https://doi.org/10.5812/ijpbs.82799
ISSN: 1735-8639
Depositing User: مهندس مهدی شریفی
URI: http://eprints.medilam.ac.ir/id/eprint/2732

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