Identifying the Symptom Severity in Obsessive-Compulsive Disorder for Classification and Prediction: An Artificial Neural Network Approach
Joint Authors
Shahzad, Mirza Naveed
Suleman, Muhammad
Ahmed, Mirza Ashfaq
Riaz, Amna
Fatima, Khadija
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-22
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The present study is aimed at identifying the most prominent determinants of OCD along with their strength to classify the OCD patients from healthy controls.
The data for this cross-sectional study were collected from 200 diagnosed OCD patients and 400 healthy controls.
The respondents were selected through purposive sampling and interviewed by using the Y-BOCS scale with the addition of a factor, worth of an individual in his family.
The validity and reliability of data were assessed through Cronbach’s alpha and confirmatory factor analysis.
Artificial Neural Network (ANN) modeling was adopted to determine threatening determinants along with their strength to predict OCD in an individual.
The results of ANN modeling depicted 98% accurate classification of OCD patients from healthy controls.
The most contributing factors in determining the OCD patients according to normalized importance were the contamination and cleaning (100%); symmetric and perfection (72.5%); worth of an individual in the family (71.1%); aggressive, religious, and sexual obsession (50.5%); high-risk assessment (46.0%); and somatic obsessions and checking (24.0%).
American Psychological Association (APA)
Shahzad, Mirza Naveed& Suleman, Muhammad& Ahmed, Mirza Ashfaq& Riaz, Amna& Fatima, Khadija. 2020. Identifying the Symptom Severity in Obsessive-Compulsive Disorder for Classification and Prediction: An Artificial Neural Network Approach. Behavioural Neurology،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1138371
Modern Language Association (MLA)
Shahzad, Mirza Naveed…[et al.]. Identifying the Symptom Severity in Obsessive-Compulsive Disorder for Classification and Prediction: An Artificial Neural Network Approach. Behavioural Neurology No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1138371
American Medical Association (AMA)
Shahzad, Mirza Naveed& Suleman, Muhammad& Ahmed, Mirza Ashfaq& Riaz, Amna& Fatima, Khadija. Identifying the Symptom Severity in Obsessive-Compulsive Disorder for Classification and Prediction: An Artificial Neural Network Approach. Behavioural Neurology. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1138371
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138371