Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at, first published .
Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study

Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study

Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study


  1. Vega J, Bell B, Taylor C, Xie J, Ng H, Honary M, McNaney R. Detecting Mental Health Behaviors Using Mobile Interactions: Exploratory Study Focusing on Binge Eating. JMIR Mental Health 2022;9(4):e32146 View
  2. Taywade A, Ramasamy S. (Retracted) Internet of things assisted improved web service to optimize power-sharing for a gadget application. Journal of Electronic Imaging 2022;32(05) View
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  9. Philippi P, Baumeister H, Apolinário-Hagen J, Ebert D, Hennemann S, Kott L, Lin J, Messner E, Terhorst Y. Acceptance towards digital health interventions – Model validation and further development of the Unified Theory of Acceptance and Use of Technology. Internet Interventions 2021;26:100459 View
  10. Hossain E, Alazeb A, Almudawi N, Almakdi S, Alshehri M, Gazi Golam Faruque M, Rahman W. Forecasting Mental Stress Using Machine Learning Algorithms. Computers, Materials & Continua 2022;72(3):4945 View
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  13. Girousse E, Vuillerme N. The Use of Passive Smartphone Data to Monitor Anxiety and Depression Among College Students in Real-World Settings: Protocol for a Systematic Review. JMIR Research Protocols 2022;11(12):e38785 View
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  17. Attai K, Amannejad Y, Vahdat Pour M, Obot O, Uzoka F. A Systematic Review of Applications of Machine Learning and Other Soft Computing Techniques for the Diagnosis of Tropical Diseases. Tropical Medicine and Infectious Disease 2022;7(12):398 View
  18. Yang X, Knights J, Bangieva V, Kambhampati V. Association Between the Severity of Depressive Symptoms and Human-Smartphone Interactions: Longitudinal Study. JMIR Formative Research 2023;7:e42935 View
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  23. Terhorst Y, Sander L, Ebert D, Baumeister H. Optimizing the predictive power of depression screenings using machine learning. DIGITAL HEALTH 2023;9 View
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Books/Policy Documents

  1. Terhorst Y, Knauer J, Baumeister H. Digital Phenotyping and Mobile Sensing. View
  2. Opoku Asare K, Visuri A, Vega J, Ferreira D. Wireless Mobile Communication and Healthcare. View
  3. Ahmed M, Hasan T, Rahman M, Ahmed N. Pervasive Computing Technologies for Healthcare. View
  4. Tahsin M, Jasim S, Naheen I. Inventive Communication and Computational Technologies. View
  5. Roy D, Roy A, Roy U. Computational Intelligence in Healthcare Informatics. View