Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41868, first published .
Prediction of Chronic Stress and Protective Factors in Adults: Development of an Interpretable Prediction Model Based on XGBoost and SHAP Using National Cross-sectional DEGS1 Data

Prediction of Chronic Stress and Protective Factors in Adults: Development of an Interpretable Prediction Model Based on XGBoost and SHAP Using National Cross-sectional DEGS1 Data

Prediction of Chronic Stress and Protective Factors in Adults: Development of an Interpretable Prediction Model Based on XGBoost and SHAP Using National Cross-sectional DEGS1 Data

Authors of this article:

Arezoo Bozorgmehr1 Author Orcid Image ;   Birgitta Weltermann1 Author Orcid Image

Journals

  1. Abd Al-Alim M, Mubarak R, M. Salem N, Sadek I. A machine-learning approach for stress detection using wearable sensors in free-living environments. Computers in Biology and Medicine 2024;179:108918 View
  2. Mikołajewski D, Piszcz A, Rojek I, Galas K. Machine Learning Supporting Virtual Reality and Brain–Computer Interface to Assess Work–Life Balance Conditions for Employees. Electronics 2024;13(22):4489 View