This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (2939) mHealth for Data Collection and Research (955) Depression and Mood Disorders; Suicide Prevention (1363) Methods and New Tools in Mental Health Research (454) Psychotic Disorders (160) Diagnostic Tools in Mental Health (242) Digital Biomarkers and Digital Phenotyping (191) Ecological Momentary Assessment (EMA) (309)

Published on in Vol 20, No 7 (2018): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9775, first published .
Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study

Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study

Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study

Authors of this article:

John Zulueta1 Author Orcid Image ;   Andrea Piscitello1 Author Orcid Image ;   Mladen Rasic1 Author Orcid Image ;   Rebecca Easter1 Author Orcid Image ;   Pallavi Babu2 Author Orcid Image ;   Scott A Langenecker1 Author Orcid Image ;   Melvin McInnis2 Author Orcid Image ;   Olusola Ajilore1 Author Orcid Image ;   Peter C Nelson1 Author Orcid Image ;   Kelly Ryan2 Author Orcid Image ;   Alex Leow1 Author Orcid Image
Article Authors Cited by (131) Tweetations (35) Metrics

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