Ontology highlight
ABSTRACT: Purpose
Cancer registries are often asked to present cancer data for small geographic areas to inform and facilitate targeted interventions and prevention programs. However, it is challenging to compute and visualize reliable cancer estimates for areas with small case counts and populations to support cancer control planning.Methods
We used a Bayesian hierarchical model that borrows strength from neighboring areas and over time to produce cancer estimates for small areas. We developed a visual analytics platform to present these estimates in interactive graphics that demonstrate risk in small areas. In a user-centered design process, development of the tool was informed by cancer registry and public health professionals through focus groups and surveys.Results
The C
SUBMITTER: Gerdes EW
PROVIDER: S-EPMC11601841 | biostudies-literature | 2024 Nov
REPOSITORIES: biostudies-literature