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Value in Health
Traditional analytic methods are often ill-suited to the evolving world of health care big data characterized by massive volume, complexity, and velocity. In particular, methods are needed that can estimate models efficiently using very large datasets containing healthcare utilization data, clinical data, data from personal devices, and many other sources. Although very large, such datasets can also be quite sparse (e.g., device data may only be available for a small subset of individuals),doi:10.1016/j.jval.2014.12.005 pmid:25773546 fatcat:wzkwz7yxuzgc5h3blttxkm4kyq