Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48444, first published .
Patient Health Questionnaire-9 Item Pairing Predictiveness for Prescreening Depressive Symptomatology: Machine Learning Analysis

Patient Health Questionnaire-9 Item Pairing Predictiveness for Prescreening Depressive Symptomatology: Machine Learning Analysis

Patient Health Questionnaire-9 Item Pairing Predictiveness for Prescreening Depressive Symptomatology: Machine Learning Analysis

Journals

  1. Wu Y, Ye Z, Wang Z, Duan S, Zhu J, Fang Y. Examining individual and contextual predictors of disability in Chinese older adults: A machine learning approach. International Journal of Medical Informatics 2024;191:105552 View
  2. Nejadshamsi S, Karami V, Ghourchian N, Armanfard N, Bergman H, Grad R, Wilchesky M, Khanassov V, Vedel I, Abbasgholizadeh Rahimi S. Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study. JMIR Aging 2025;8:e67715 View
  3. Ward S, Patel S, Singh K. The Mind and Spine Connection. Contemporary Spine Surgery 2025;26(5):1 View