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• W2917124249 abstract "Translation of traumatic brain injury (TBI) research findings from bench to bedside involves aligning multi-species data across diverse data types including imaging and molecular biomarkers, histopathology, behavior, and functional outcomes. In this review we argue that TBI translation should be acknowledged for what it is: a problem of big data that can be addressed using modern data science approaches. We review the history of the term big data, tracing its origins in Internet technology as data that are big according to the 4Vs of volume, velocity, variety, veracity and discuss how the term has transitioned into the mainstream of biomedical research. We argue that the problem of TBI translation fundamentally centers around data variety and that solutions to this problem can be found in modern machine learning and other cutting-edge analytical approaches. Throughout our discussion we highlight the need to pull data from diverse sources including unpublished data (dark data) and long-tail data (small, specialty TBI datasets undergirding the published literature). We review a few early examples of published articles in both the pre-clinical and clinical TBI research literature to demonstrate how data reuse can drive new discoveries leading into translational therapies. Making TBI data resources more Findable, Accessible, Interoperable, and Reusable (FAIR) through better data stewardship has great potential to accelerate discovery and translation for the silent epidemic of TBI." @default.
• W2917124249 created "2019-03-02" @default.
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• W2917124249 creator A5087351342 @default.
• W2917124249 date "2020-11-15" @default.
• W2917124249 modified "2023-09-26" @default.
• W2917124249 title "Data Dissemination: Shortening the Long Tail of Traumatic Brain Injury Dark Data" @default.
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• W2917124249 doi "https://doi.org/10.1089/neu.2018.6192" @default.
• W2917124249 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7698976" @default.
• W2917124249 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30794049" @default.
• W2917124249 hasPublicationYear "2020" @default.
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