Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) - OVERALL
Project Number5U54EB020404-05
Former Number1U54HG008073-01
Contact PI/Project LeaderKUMAR, SANTOSH
Awardee OrganizationUNIVERSITY OF MEMPHIS
Description
Abstract Text
DESCRIPTION (provided by applicant): Rapid advances in technology, are leading to field-deployable mobile sensing devices that can now be used to quantify complex dynamics across time of key physical, biological, behavioral, social, and environmental factors that contribute to
health and disease risk. These data will enable us to break through to the next level of biomedical understanding of causation in complex disorders. While ongoing efforts have made significant strides in the analysis of "big data" in the areas of genomics, imaging, and EHR, significant new investment is needed to develop and disseminate data analytics tools specific to the unique features of mobile sensor data (e.g., high volume, velocity, variety, variability, and versatility) to convert this wealth of data into information, knowledge, and action. Investment in strong, open, scientific, and computational infrastructure for mobile "big data" at this early stag promises outsize returns to advance science and improve health. The Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K) will generate generalizable theory, methods, tools, and software, to address major barriers to processing complex mobile sensor data and its use in biomedical knowledge discovery and just-in-time care delivery, laying the foundation for P5 Medicine. It will develop and implement a standards-based, interoperable, extensible and open-source big data software platform for efficient implementation of MD2K data analytics. The MD2K Center will demonstrate the feasibility, utility, and generalizability of the MD2K approach by implementing the entire MD2K data analytics system in the context of two biomedical applications - reducing relapse among abstinent daily smokers and reducing readmission among congestive heart failure (CHF) patients. All the tools and software developed by the Center will be freely available as standards-compliant and open-source with documentation to engage data science researchers in advancing the science of MD2K and its integration with other biomedical big data such as EHRs, genomics, and imaging. The Center will provide training materials to help biomedical researchers install the MD2K software on their mobile devices and servers to collect mobile sensor data and analyze these data for biomedical discovery.
Public Health Relevance Statement
PUBLIC HEALTH RELEVANCE: By enabling the use of mobile sensor data to detect and predict person-specific disease risk factors ahead of the onset of adverse clinical events, this project will make it possible to intervene anytime, anywhere, to anticipate and prevent disease complications at the earliest time point, ultimately supporting wellness. These tools, made freely available, will reduce the burden of complex chronic disorders on health and healthcare.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AddressAlgorithmsArchitectureAreaAsthmaBackBehaviorBehavioralBig DataBiologicalBiomedical ResearchCardiovascular DiseasesChronic DiseaseClinicalCommunitiesComplexComputer softwareComputing MethodologiesCongestive Heart FailureDataData AnalysesData AnalyticsData ReportingData ScienceDevicesDiabetes MellitusDiseaseDocumentationE-learningEducational CurriculumEnvironmentEnvironmental Risk FactorEtiologyEventFoundationsFundingGeneticGenomicsGoalsHealthHealthcareImageIndividualInterventionInvestmentsKnowledgeKnowledge DiscoveryMalignant NeoplasmsMeasuresMedicineMental DepressionMethodsMiningObesityParticipantPatient CarePatient MonitoringPatient Self-ReportPatientsPatternPersonsPopulationPrevention strategyPreventiveRelapseResearch PersonnelResearch TrainingRisk FactorsScienceSemanticsSeriesSmokerStandardizationStructureSystemTechnologyTimeTrainingUnited StatesUnited States National Institutes of HealthVisionVisualization softwareanalytical toolbasebig biomedical databurden of illnesscare deliverycare providerscomputer infrastructuredata to knowledgedesigndisorder riskexperiencehandheld mobile devicehospital readmissionimprovedinstructorinteroperabilitymHealthopen sourcepreventpublic health relevancesensorsocialsoftware developmenttheoriestooltreatment responseusability
National Institute of Biomedical Imaging and Bioengineering
CFDA Code
286
DUNS Number
055688857
UEI
F2VSMAKDH8Z7
Project Start Date
29-September-2014
Project End Date
30-September-2020
Budget Start Date
01-June-2018
Budget End Date
30-September-2020
Project Funding Information for 2018
Total Funding
$881,788
Direct Costs
$1,680,063
Indirect Costs
$204,435
Year
Funding IC
FY Total Cost by IC
2018
National Institute of Neurological Disorders and Stroke
$881,788
Year
Funding IC
FY Total Cost by IC
Sub Projects
No Sub Projects information available for 5U54EB020404-05
Publications
Publications are associated with projects, but cannot be identified with any particular year of the project or fiscal year of funding. This is due to the continuous and cumulative nature of knowledge generation across the life of a project and the sometimes long and variable publishing timeline. Similarly, for multi-component projects, publications are associated with the parent core project and not with individual sub-projects.
No Publications available for 5U54EB020404-05
Patents
No Patents information available for 5U54EB020404-05
Outcomes
The Project Outcomes shown here are displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed are those of the PI and do not necessarily reflect the views of the National Institutes of Health. NIH has not endorsed the content below.
No Outcomes available for 5U54EB020404-05
Clinical Studies
No Clinical Studies information available for 5U54EB020404-05
News and More
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History
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Similar Projects
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