Leveraging domain knowledge to facilitate visual exploration of large population datasets.
Year: 2013
Type: article
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.
Source: Europe PMC (PubMed Central)
Authors: William Hsu, Alex A T Bui
Institution: University of California, Los Angeles
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W171869951