Detecting Depression in Elderly People by Using Artificial Neural Network

author

  • mojgan mirza Department of Psychology, Faculty of Humanities, Gonbad Kavous University, Gonbad Kavous, Iran
Abstract:

Introduction: The possibility of depression is common in the elderly. Novel technologies allow us to monitor people related to depression. Hence, a model was provided to detect depression in elderly based on artificial neural network (ANN). Methods: The present study is an applied descriptive-survey research. Forty elderly people were randomly selected from the Elderly Care Center in Gonbad Kavous, Golestan, Iran in 2019. Data were obtained through interview. The data were randomly divided in to two groups of training and testing. In training phase by using first dataset (70%), three layers network is considered. Interrelation weights between variables, optimum transfer function and optimum number of hidden layer were obtained. The sum of squared errors, receiver operating characteristic curve criterion and accuracy were used to select the optimum ANN. The optimum model tested and validated (p < 0.001) with second dataset (30%). Results: The sigmoid transfer function in hidden and output layers with 5 nods (SSE = 131), one hidden layer with 15 neurons was considered as optimum model. Receiver operating characteristic curve criterion and accuracy were obtained equal to 0.913 and 94.79% respectively. The confusion matrix was showed high sensitivity (97.45%) and specificity (99.25%) in the diagnosis of depression. Age, gender, income, polarity outgoing messages to family, incoming calls, time active in the day, polarity incoming messages from family, time sleep in the day were obtained as a significant set for input layer of the optimum model. In addition, the optimum model has been quite successful in identifying normal and depressed elderly. Conclusion: This research applied an ANN model for detection of depression in the elderly. ANN can be used as a computational tools for early diagnosis of depression in the elderly People.  

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

scour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network

today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...

پیش بینی ورشکستگی شرکت های پذیرفته شده در بورس اوراق بهادار تهران با استفاده از شبکه های عصبی مصنوعی forecasting corporation bankruptcy by using artificial neural network

استفاده از نسبت های مالی برای پیش بینی ورشکستگی شرکتها، همیشه مورد توجه دانشگاهیان و بنگاه های اقتصادی، بویژه بانک ها و سایر نهادهای مالی بوده است. پیش بینی به موقع میتواند تصمیم گیران را در یافتن راه حل و پیشگیری از ورشکستگی، یاری نماید. همچنین، این مدل ها کاربرد بسیار زیادی در رتبه بندی اعتباری و نحوه توزیع تسهیلات بانکی دارد. در چنین مطالعاتی معمولات از مدل های آماری مانند تحلیل ممیز چندگانه...

15 صفحه اول

Distillation Column Identification Using Artificial Neural Network

  Abstract: In this paper, Artificial Neural Network (ANN) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. The actual input-output data of the system were measured in order to be used for system identification based on root mean square error (RMSE) minimization approach. It was shown that the designed recurrent neural network is able to pr...

full text

Estimation of pigment magnitudes in synthetic leather by using scanner and artificial neural network

In the present work the magnitudes of pigments in the synthetic leather, were measured by means of scanner. Initially synthetic leather samples pigmented by three different pigments of yellow, blue and red colors were prepared. Then the pigmented samples were scanned, and the values of RGB of images were calculated. The artificial neural network (ANN) method used to make relation between RGB va...

full text

Stream Flow Prediction in Flood Plain by Using Artificial Neural Network (Case Study: Sepidroud Watershed)

In order to determine hydrological behavior and water management of Sepidroud River (North of Iran-Guilan) the present study has focused on stream flow prediction by using artificial neural network. Ten years observed inflow data (2000-2009) of Sepidroud River were selected; then these data have been forecasted by using neural network. Finally, predicted results are compared to the observed dat...

full text

Predicting Force in Single Point Incremental Forming by Using Artificial Neural Network

In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 6  issue 2

pages  103- 108

publication date 2020-12

By following a journal you will be notified via email when a new issue of this journal is published.

Keywords

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023