Interactive visual analysis of heterogeneous cohort-study data.

Medical cohort studies enable the study of medical hypotheses with many samples. Often, these studies acquire a large amount of heterogeneous data from many subjects. Usually, researchers study a specific data subset to confirm or reject specific hypotheses. A new approach enables the interactive visual exploration and analysis of such data, helping to generate and validate hypotheses. A data-cube-based model handles partially overlapping data subsets during the interactive visualization. This model enables seamless integration of the heterogeneous data and the linking of spatial and nonspatial views of the data. Researchers implemented this model in a prototype application and used it to analyze data acquired in a cohort study on cognitive aging. Case studies employed the prototype to study aspects of brain connectivity, demonstrating the model's potential and flexibility.