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Tell me your apps and I will tell you your mood: correlation of apps usage with bipolar disorder state.

, , , , , , and . PETRA, page 19:1-19:7. ACM, (2014)

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Impact factor analysis: combining prediction with parameter ranking to reveal the impact of behavior on health outcome., , , , and . Personal and Ubiquitous Computing, 19 (2): 355-365 (2015)Personalizing Mental Health: A Feasibility Study of a Mobile Behavioral Activation Tool for Depressed Patients., , , , , and . PervasiveHealth, page 282-291. ACM, (2019)Wearable Computing Technology for Assessment of Cognitive Functioning of Bipolar Patients and Healthy Controls., , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (4): 129:1-129:22 (2020)Supporting disease insight through data analysis: refinements of the monarca self-assessment system., , , , and . UbiComp, page 133-142. ACM, (2013)Association of hormonal contraception with depression, , , and . JAMA psychiatry, 73 (11): 1154--1162 (2016)MUBS: A Personalized Recommender System for Behavioral Activation in Mental Health., , , , , and . CHI, page 1-13. ACM, (2020)Tell me your apps and I will tell you your mood: correlation of apps usage with bipolar disorder state., , , , , , and . PETRA, page 19:1-19:7. ACM, (2014)Benefits of Using Activity Recommender Technology for Self-management of Depressive Symptoms., , , and . ACM Trans. Comput. Heal., 2 (4): 31:1-31:21 (2021)High familial risk for mood disorder is associated with low dorsolateral prefrontal cortex serotonin transporter binding., , , , , , , , , and . NeuroImage, 46 (2): 360-366 (2009)The Center for Integrated Molecular Brain Imaging (Cimbi) database., , , , , , , , , and 16 other author(s). NeuroImage, (2016)