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:: Volume 24, Issue 4 (11-2016) ::
sjimu 2016, 24(4): 11-20 Back to browse issues page
Use of Artificial Neural Network Versus Logistic Regression to Predict Post-Traumatic Mental Disorders
Elham Shafiei1, Esmaeil Fakharian 2, Abdollah Omidi3, Hossein Akbari4, Ali Delpisheh5, Arash Nademi6
1- Trauma Research Center, Kashan University of Medical Sciences, Kashan, Iran
2- Trauma Research Center, Kashan University of Medical Sciences, Kashan, Iran , efakharian@gmail.com
3- Dept of Clinical Psychology, Kashan University of Medical Sciences, Kashan, Iran
4- Dept of Biostatistics and Public Health, Faculty of Health, Kashan University of Medical Sciences, Kashan, Iran
5- Prevention of Psychosocial Injuries Research Centre, Ilam University of Medical Sciences, Ilam, Iran
6- Dept of Statistics, Islamic Azad University, Ilam Branch, Ilam, Iran
Abstract:   (4877 Views)

Introduction: Nowadays, the artificial neural networks have received much attention in predicting the effects of multiple variables and complex relationships in aparticular variables. In this study, we have focused on the use of artificial neural network versus logistic regression to predict post-traumatic mental disorders.

Materials & methods: In a prospective cohort study, we covered 100 trauma patients admitted to the trauma center of Shahid Beheshti Hospital of Kashan during a six month period. The patients were then randomly divided into two training (n=50) andexperimental(n=50) groups. 14 variablesincluding age, sex, occupation, education level, marital status, socioeconomic status, history ofmental illnessin theimmediate family, history of being hospitalized in neurosurgeryunit, historyof trauma,history ofunderlying disease, history of psychologicaldrug use, history of anesthesia, history of alcohol use, and history of substance abuse were totally investigated. 300artificial neural networksandlogistic regressions were studied in the first group and then the predicted values were compared in the second group using the two models. The ROC curve and classification accuracy tool were applied to estimate the predictive power of mental disorder.

Findings: The results showed that the accurate index for predicting the disorder was90.65% for the neural network model, while it was 75.96% for the logistic regression model.

Discussion & conclusions: The artificial neural network models appeared to bemore powerful in predictingmental disorder versus the logistic regression model.

Keywords: Anticipation, Mental illness, Artificial neural network, Logistic regression, Mildtraumatic brain injury
Full-Text [PDF 504 kb]   (2405 Downloads)    
Type of Study: Applicable | Subject: immunology
Received: 2015/07/4 | Accepted: 2016/02/1 | Published: 2016/10/23
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Shafiei E, Fakharian E, Omidi A, Akbari H, Delpisheh A, Nademi A. Use of Artificial Neural Network Versus Logistic Regression to Predict Post-Traumatic Mental Disorders. sjimu. 2016; 24 (4) :11-20
URL: http://sjimu.medilam.ac.ir/article-1-2870-en.html


Volume 24, Issue 4 (11-2016) Back to browse issues page
مجله علمی پزوهشی دانشگاه علوم پزشکی ایلام scientific journal of ilam university of medical sciences
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