Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53714, first published .
Machine Learning, Deep Learning, and Data Preprocessing Techniques for Detecting, Predicting, and Monitoring Stress and Stress-Related Mental Disorders: Scoping Review

Machine Learning, Deep Learning, and Data Preprocessing Techniques for Detecting, Predicting, and Monitoring Stress and Stress-Related Mental Disorders: Scoping Review

Machine Learning, Deep Learning, and Data Preprocessing Techniques for Detecting, Predicting, and Monitoring Stress and Stress-Related Mental Disorders: Scoping Review

Moein Razavi   1, 2 , BSc, ME, PhD ;   Samira Ziyadidegan   1 , BSc, MSc, PhD ;   Ahmadreza Mahmoudzadeh   3 , BSc, MSc, MS, PhD ;   Saber Kazeminasab   4 , BSc, MSc, PhD ;   Elaheh Baharlouei   5 , BSc, MSc, PhD ;   Vahid Janfaza   2 , BSc, MSc, PhD ;   Reza Jahromi   1, 2 , BSc, MSc, MCS, PhD ;   Farzan Sasangohar   1 , BA, BCS, MASc, SM, PhD

1 Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States

2 Department of Computer Science and Engineering, Texas A&M University, College Station, TX, United States

3 Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX, United States

4 Harvard Medical School, Harvard University, Boston, MA, United States

5 Department of Computer Science, University of Houston, Houston, TX, United States

Corresponding Author:

  • Farzan Sasangohar, BA, BCS, MASc, SM, PhD
  • Department of Industrial and Systems Engineering
  • Texas A&M University
  • 3131 TAMU
  • College Station, TX, 77843-3131
  • United States
  • Phone: 1 979 458 2337
  • Email: sasangohar@tamu.edu