title: Leveraging domain knowledge to facilitate visual exploration of large population datasets.
abstract: Observational patient data provides an unprecedented opportunity to gleam new insights into diseases and assess patient quality of care, but a challenge lies in matching our ability to collect data with a comparable ability to understand and apply this information. Visual analytic techniques are promising as they permit the exploration and manipulation of complex datasets through a graphical user interface. Nevertheless, current visualization tools rely on users to manually configure which aspects of the dataset are shown and how they are presented. In this paper, we describe an approach that utilizes characteristics of the data and domain knowledge to assist users with summarizing the information space of a large population. We present a representation that captures contextual information about the data and constructs that operate on this information to tailor the data's presentation. We describe a use case of this approach in exploring a claims dataset of individuals with spinal dysraphism.
authors.affiliation: Medical Imaging Informatics Group, Dept of Radiological Sciences, University of California, Los Angeles.
authors.forename: William
authors.initials: W
authors.lastname: Hsu
authors.affiliation: Medical Imaging Informatics Group, Dept of Radiological Sciences, University of California, Los Angeles.
authors.forename: Alex A T
authors.initials: AA
authors.lastname: Bui
mesh_terms: D003196:Computer Graphics; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D057286:Electronic Health Records; D006801:Humans; D007345:Insurance Claim Review