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Understanding behavioral dynamics of social anxiety among college students through smartphone sensors.

, , , , , , и . Inf. Fusion, (2019)

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R. A. A. Bowler

°Ake °Akerström

Mohamed A A Anndif

Eltohamy A A Yousef

A Wolff

 

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Offline Contextual Multi-armed Bandits for Mobile Health Interventions: A Case Study on Emotion Regulation., , , , , и . RecSys, стр. 249-258. ACM, (2020)Detecting Social Contexts from Mobile Sensing Indicators in Virtual Interactions with Socially Anxious Individuals., , , , , , , , и . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 7 (3): 134:1-134:26 (сентября 2023)Contextual Analysis to Understand Compliance with Smartphone-based Ecological Momentary Assessment., , , , , , и . PervasiveHealth, стр. 232-238. ACM, (2018)A Weakly Supervised Learning Framework for Detecting Social Anxiety and Depression., , , , и . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2 (2): 81:1-81:26 (2018)Cluster-based Approach to Improve Affect Recognition from Passively Sensed Data., , , , , , , и . CoRR, (2018)DEMONS: an integrated framework for examining associations between physiology and self-reported affect tied to depressive symptoms., , , , , и . UbiComp Adjunct, стр. 1139-1143. ACM, (2016)Assessing social anxiety using gps trajectories and point-of-interest data., , , , , , , и . UbiComp, стр. 898-903. ACM, (2016)Predicting Subjective Measures of Social Anxiety from Sparsely Collected Mobile Sensor Data., , , , , , и . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (3): 109:1-109:24 (2020)Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline., , , , , , , , и . EMBC, стр. 1-6. IEEE, (2023)Identification of Imminent Suicide Risk Among Young Adults using Text Messages., , , , и . CHI, стр. 413. ACM, (2018)