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

Mobile Health (mhealth) (2765) e-Mental Health and Cyberpsychology (1402)

Published on in Vol 15, No 7 (2013): July

Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services

Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services

Maximizing the Value of Mobile Health Monitoring by Avoiding Redundant Patient Reports: Prediction of Depression-Related Symptoms and Adherence Problems in Automated Health Assessment Services

Authors of this article:

John D Piette1 ;   Jeremy B Sussman1 ;   Paul N Pfeiffer2 ;   Maria J Silveira1 ;   Satinder Singh3 ;   Mariel S Lavieri4
Article Authors Cited by (11) Tweetations (5) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.