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Connecting and linking neurocognitive, digital phenotyping, physiologic, psychophysical, neuroimaging, genomic, & sensor data with survey data
- Source :
- EPJ Data Science, Vol 10, Iss 1, Pp 1-16 (2021), Epj Data Science
- Publication Year :
- 2021
- Publisher :
- SpringerOpen, 2021.
-
Abstract
- Combining survey data with alternative data sources (e.g., wearable technology, apps, physiological, ecological monitoring, genomic, neurocognitive assessments, brain imaging, and psychophysical data) to paint a complete biobehavioral picture of trauma patients comes with many complex system challenges and solutions. Starting in emergency departments and incorporating these diverse, broad, and separate data streams presents technical, operational, and logistical challenges but allows for a greater scientific understanding of the long-term effects of trauma. Our manuscript describes incorporating and prospectively linking these multi-dimensional big data elements into a clinical, observational study at US emergency departments with the goal to understand, prevent, and predict adverse posttraumatic neuropsychiatric sequelae (APNS) that affects over 40 million Americans annually. We outline key data-driven system challenges and solutions and investigate eligibility considerations, compliance, and response rate outcomes incorporating these diverse “big data” measures using integrated data-driven cross-discipline system architecture.
- Subjects :
- 020205 medical informatics
Computer science
Physiological
Big data
Wearable technologies
Digital phenotyping
02 engineering and technology
lcsh:Computer applications to medicine. Medical informatics
03 medical and health sciences
0302 clinical medicine
Passive data
0202 electrical engineering, electronic engineering, information engineering
030212 general & internal medicine
Wearable technology
Response rate (survey)
business.industry
Data stream mining
Linkage
Psychophysical
Systems
Regular Article
Data-driven
Interconnections
Data science
Neurocognitive
Computer Science Applications
Computational Mathematics
Modeling and Simulation
Systems architecture
Survey data collection
lcsh:R858-859.7
Observational study
business
Subjects
Details
- Language :
- English
- ISSN :
- 21931127
- Volume :
- 10
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- EPJ Data Science
- Accession number :
- edsair.doi.dedup.....b76b253bafa63e3bebe3a25fd909d8af