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Computers in Human Behavior|November 15, 2021
Using Smartphone App Use and Lagged-Ensemble Machine Learning for the Prediction of Work Fatigue and BoredomDamien Lekkas, George D Price, Nicholas C JacobsonBehaviour Research and Therapy|August 6, 2023
Depression deconstructed: Wearables and passive digital phenotyping for analyzing individual symptomsDamien Lekkas, Joseph A Gyorda, George D Price, et al.Psychiatry Research|January 9, 2024
Detecting major depressive disorder presence using passively-collected wearable movement data in a nationally-representative sampleGeorge D Price, Michael V Heinz, Amanda C Collins, et al.The Journal of Positive Psychology|June 10, 2024
Predicting Individual Response to a Web-Based Positive Psychology Intervention: A Machine Learning ApproachAmanda C Collins, George D Price, Rosalind J Woodworth, et al.Journal of Medical Internet Research|December 21, 2021
Using the COVID-19 Pandemic to Assess the Influence of News Affect on Online Mental Health-Related Search Behavior Across the United States: Integrated Sentiment Analysis and the Circumplex Model of AffectDamien Lekkas, Joseph A Gyorda, George D Price, et al.Frontiers in Psychiatry|August 29, 2022
Predicting symptom response and engagement in a digital intervention among individuals with schizophrenia and related psychosesGeorge D Price, Michael V Heinz, Matthew D Nemesure, et al.Journal of Psychopathology and Clinical Science|October 21, 2024
Use of passively collected actigraphy data to detect individual depressive symptoms in a clinical subpopulation and a general populationGeorge D Price, Amanda C Collins, Daniel M Mackin, et al.Translational Psychiatry|December 9, 2023
Using digital phenotyping to capture depression symptom variability: detecting naturalistic variability in depression symptoms across one year using passively collected wearable movement and sleep dataGeorge D Price, Michael V Heinz, Seo Ho Song, et al.Journal of Affective Disorders|August 14, 2022
An unsupervised machine learning approach using passive movement data to understand depression and schizophreniaGeorge D Price, Michael V Heinz, Daniel Zhao, et al.Journal of Affective Disorders|March 1, 2023
Leveraging deep learning models to understand the daily experience of anxiety in teenagers over the course of a yearBrian Wang, Matthew D Nemesure, Chloe Park, et al.Pageof 3