Comparison of Artificial Neural Network and Logistic Regression Models for Prediction of Psychological Symptom Six Months after Mild Traumatic Brain Injury

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SHAFIEI ELHAM; FAKHARIAN ESMAEIL; OMIDI ABDOLLAH; AKBARI HOSSEIN; DELPISHEH ALI; NADEMI ARASH

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Journal Paper

Paper Information

Journal: Iranian Journal of Psychiatry and Behavioral Sciences Year:2017 | Volume:11 | Issue:3 Page(s): 1-6

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Title

Comparison of Artificial Neural Network and Logistic Regression Models for Prediction of Psychological Symptom Six Months after Mild Traumatic Brain Injury

Author(s)

Keywords

Artificial Neural Network

Logistic Regression

Mental Disorder

Mild Traumatic Brain Injury

Prediction

Principle Component Analysis

Psychological Symptom

Abstract

Background: Nowadays, outcome Prediction models using Logistic Regression (LR) and Artificial Neural Network (ANN) analysis have been developed in many areas of healthcare research. Objectives: In this study, we have compared the performance of multivariable LR and ANN models, in Prediction of Psychological Symptoms six months after Mild Traumatic Brain Injury. Methods: In a prospective cohort study, information of 100 Mild Traumatic Brain Injury patients, during a six months period between 2014 and 2016 were included. Data were divided into two training (n = 50) and testing (n = 50) groups, randomly. 300 ANNs and LRs were studied in the first group and then the predicted values were compared in the second group using the two final models. The receiver operating characteristic (ROC) curve and accuracy rate were used to compare these models. Results: The results showed that accuracy rate for the neural network model was 90. 65%, while it was 75. 96% for the LR model. Conclusions: The ANN models appeared to be more powerful in predicting Psychological Symptoms versus the LR models.

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APA: Copy

SHAFIEI, ELHAM, FAKHARIAN, ESMAEIL, OMIDI, ABDOLLAH, AKBARI, HOSSEIN, DELPISHEH, ALI, & NADEMI, ARASH. (2017). Comparison of Artificial Neural Network and Logistic Regression Models for Prediction of Psychological Symptom Six Months after Mild Traumatic Brain Injury. IRANIAN JOURNAL OF PSYCHIATRY AND BEHAVIORAL SCIENCES (IJPBS), 11(3), 1-6. SID. https://sid.ir/paper/312342/en

Vancouver: Copy

SHAFIEI ELHAM, FAKHARIAN ESMAEIL, OMIDI ABDOLLAH, AKBARI HOSSEIN, DELPISHEH ALI, NADEMI ARASH. Comparison of Artificial Neural Network and Logistic Regression Models for Prediction of Psychological Symptom Six Months after Mild Traumatic Brain Injury. IRANIAN JOURNAL OF PSYCHIATRY AND BEHAVIORAL SCIENCES (IJPBS)[Internet]. 2017;11(3):1-6. Available from: https://sid.ir/paper/312342/en

IEEE: Copy

ELHAM SHAFIEI, ESMAEIL FAKHARIAN, ABDOLLAH OMIDI, HOSSEIN AKBARI, ALI DELPISHEH, and ARASH NADEMI, “Comparison of Artificial Neural Network and Logistic Regression Models for Prediction of Psychological Symptom Six Months after Mild Traumatic Brain Injury,” IRANIAN JOURNAL OF PSYCHIATRY AND BEHAVIORAL SCIENCES (IJPBS), vol. 11, no. 3, pp. 1–6, 2017, [Online]. Available: https://sid.ir/paper/312342/en

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