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Machine Evaluation of Catchment Area Relevance through Text Mining.
Arlen, Philip A; Chakko, Joseph; DeGennaro, Geoffrey; Kobetz, Erin; Mahal, Brandon.
Afiliação
  • Arlen PA; University of Miami, Sylvester Comprehensive Cancer Center, Miami, FL.
  • Chakko J; University of Miami, Sylvester Comprehensive Cancer Center, Miami, FL.
  • DeGennaro G; University of Miami, Sylvester Comprehensive Cancer Center, Miami, FL.
  • Kobetz E; University of Miami, Sylvester Comprehensive Cancer Center, Miami, FL.
  • Mahal B; University of Miami, Sylvester Comprehensive Cancer Center.
Crit Rev Oncog ; 29(3): 1-4, 2024.
Article em En | MEDLINE | ID: mdl-38683150
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mineração de Dados Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Crit Rev Oncog Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Mineração de Dados Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Crit Rev Oncog Ano de publicação: 2024 Tipo de documento: Article