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The Warfighter Analytics using Smart Phones for Health (WASH) program recruited 25,000 participants across the United States to download and run a newly designed cell phone app named Health & Injury Prediction and Prevention Over Complex Reasoning and Analytic Techniques Integrated on a Cell Phone App (HIPPOCRATIC App) (Android and iOS) on their personal devices and allow specific and partially-prompted data acquisition that ranges from their answers to survey question to sensor data recording at various activity contexts.

The effect of mood and mental on human activity, whether it is smartphone use activity or actual physical activity, has been an active research track for decades. Human activity modeling and recognition may be performed using wearable sensors and/or smartphone sensors, and our study deals with the latter.

This research was inspired by the fact that almost everyone nowadays has a smartphone that they are constantly using, which makes accessing valuable data to analyze and improve people's health an easy-to-achieve task. With the multidisciplinary expertise in our team, we are developing and deploying state-of-the-art data analytics and machine learning pipelines to provide tools for better mental health diagnostics. 

1. Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants (retention study)
   1. https://github.com/Sage-Bionetworks/digitalHealth_RetentionAnalysis_PublicRelease (code associated with the above study)
   2. https://github.com/Sage-Bionetworks/digitalHealth_RetentionAnalysis_PublicRelease/blob/master/analysis/timeToEvent_TRUE.Right.CensoringApproach.R (code associated with the above study)
2. An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study (compliance study)

(Anything that you think is relevant that doesn’t fit under any of the sections above.)