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

Foundations of AI (57) Artificial Intelligence (2136)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55840, first published .
Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

Predicting Workers’ Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics

Authors of this article:

Hiroki Iwamoto1 Author Orcid Image ;   Saki Nakano1 Author Orcid Image ;   Ryotaro Tajima1 Author Orcid Image ;   Ryo Kiguchi1 Author Orcid Image ;   Yuki Yoshida1 Author Orcid Image ;   Yoshitake Kitanishi1 Author Orcid Image ;   Yasunori Aoki1, 2 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Widianti D, Mahardhika Z, Modjo R. Development of a Mobile App for Occupational Stress Screening Among Female Workers: Protocol for an Exploratory Sequential Design Study. JMIR Research Protocols 2024;13:e55874 View
  2. Xu B, Lu B. Potential prediction method of sports tourism resource development based on Ga-Bp algorithm. Journal of Computational Methods in Sciences and Engineering 2025 View