Machine Evaluation of Catchment Area Relevance through Text Mining

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, ethnicall...

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Bibliographic Details
Published in:	Critical reviews in oncogenesis Vol. 29; no. 3; p. 1
Main Authors:	Arlen, Philip A, Chakko, Joseph, DeGennaro, Geoffrey, Kobetz, Erin, Mahal, Brandon
Format:	Journal Article
Language:	English
Published:	United States 2024
Subjects:	Algorithms Catchment Area, Health Data Mining Florida - epidemiology Humans Machine Learning Neoplasms - diagnosis Neoplasms - epidemiology Florida
Online Access:	Get more information
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Summary:	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.
ISSN:	0893-9675
DOI:	10.1615/CritRevOncog.2023049949