Accurate Prediction of Anxiety Levels in Asian Countries Using a Fuzzy Expert System

Mouz Ramzan; Muhammad Hamid; Amel Ali Alhussan; Hussah Nasser AlEisa; Hanaa A Abdallah

doi:10.3390/healthcare11111594

Accurate Prediction of Anxiety Levels in Asian Countries Using a Fuzzy Expert System

Healthcare (Basel). 2023 May 30;11(11):1594. doi: 10.3390/healthcare11111594.

Authors

Mouz Ramzan¹, Muhammad Hamid², Amel Ali Alhussan³, Hussah Nasser AlEisa³, Hanaa A Abdallah⁴

Affiliations

¹ Department of Computer Science, National College of Business Administration and Economics (NCBA&E), Lahore 54000, Pakistan.
² Department of Statistics and Computer Science, University of Veterinary and Animal Sciences, Lahore 54000, Pakistan.
³ Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
⁴ Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 84428, Saudi Arabia.

Abstract

Anxiety is a common mental health issue that affects a significant portion of the global population and can lead to severe physical and psychological consequences. The proposed system aims to provide an objective and reliable method for the early detection of anxiety levels by using patients' physical symptoms as input variables. This paper introduces an expert system utilizing a fuzzy inference system (FIS) to predict anxiety levels. The system is designed to address anxiety's complex and uncertain nature by utilizing a comprehensive set of input variables and fuzzy logic techniques. It is based on a set of rules that represent medical knowledge of anxiety disorders, making it a valuable tool for clinicians in diagnosing and treating these disorders. The system was tested on real datasets, demonstrating high accuracy in the prediction of anxiety levels. The FIS-based expert system offers a powerful approach to cope with imprecision and uncertainty and can potentially assist in addressing the lack of effective remedies for anxiety disorders. The research primarily focused on Asian countries, such as Pakistan, and the system achieved an accuracy of 87%, which is noteworthy.

Keywords: anxiety; anxiety prediction; fuzzy inference system; fuzzy logic.

Grants and funding

This work was supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R 308), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.