This paper is in the following e-collection/theme issue:

Development and Evaluation of Research Methods, Instruments and Tools (514) Machine Learning (1505) Anxiety and Stress Disorders (1081) Mental Health Issues in Adolescence (457) Depression and Mood Disorders; Suicide Prevention (1393)

Published on in Vol 6, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32736, first published .
Assessment and Prediction of Depression and Anxiety Risk Factors in Schoolchildren: Machine Learning Techniques Performance Analysis

Assessment and Prediction of Depression and Anxiety Risk Factors in Schoolchildren: Machine Learning Techniques Performance Analysis

Assessment and Prediction of Depression and Anxiety Risk Factors in Schoolchildren: Machine Learning Techniques Performance Analysis

Authors of this article:

Radwan Qasrawi1, 2 Author Orcid Image ;   Stephanny Paola Vicuna Polo3 Author Orcid Image ;   Diala Abu Al-Halawa4 Author Orcid Image ;   Sameh Hallaq5 Author Orcid Image ;   Ziad Abdeen4 Author Orcid Image
Article Authors Cited by (16) Tweetations (5) Metrics

Radwan Qasrawi   1, 2 , PhD ;   Stephanny Paola Vicuna Polo   3 , MA ;   Diala Abu Al-Halawa   4 , MD ;   Sameh Hallaq   5 , PhD ;   Ziad Abdeen   4 , PhD

1 Department of Computer Science, Al-Quds University, Ramallah, Palestinian Territory, Occupied

2 Department of Computer Engineering, Istinye University, Istanbul, Turkey

3 Center for Business Innovation and Technology, Al-Quds University, Jerusalem, Palestinian Territory, Occupied

4 Faculty of Medicine, Al-Quds University, Jerusalem, Palestinian Territory, Occupied

5 Al-Quds Bard College for Arts and Sciences, Al-Quds University, Jerusalem, Palestinian Territory, Occupied

Corresponding Author:

  • Radwan Qasrawi, PhD
  • Department of Computer Science
  • Al-Quds University
  • Schools Street, Number 140, 5th FL
  • Ramallah, 51000
  • Palestinian Territory, Occupied
  • Phone: 1 970592660417
  • Email: radwan@staff.alquds.edu