Machine Evaluation of Catchment Area Relevance through Text Mining

Crit Rev Oncog. 2024;29(3):1-4. doi: 10.1615/CritRevOncog.2023049949.

Abstract

The University of Miami Sylvester Comprehensive Cancer Center Community Outreach and Engagement Office has developed an algorithm to aid in identifying catchment area relevant trials. We have developed this tool to capture a catchment area (South Florida) that represents the most racially, ethnically, and geographically diverse region in the US. Unfortunately, the area's tumor burden is also significant with many notable disparities, necessitating a prioritization of trials within Sylvester's catchment area. These trials address the needs of the population Sylvester serves by targeting cancers that are locally prevalent.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Catchment Area, Health
  • Data Mining*
  • Florida / epidemiology
  • Humans
  • Machine Learning
  • Neoplasms / diagnosis
  • Neoplasms / epidemiology