Utility of machine learning in developing a predictive model for early-age-onset colorectal neoplasia using electronic health records

BACKGROUND AND AIMS: The incidence of colorectal cancer (CRC) is increasing in adults younger than 50, and early screening remains challenging due to cost and under-utilization. To identify individuals aged 35–50 years who may benefit from early screening, we developed a prediction model using machi...

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Detalles Bibliográficos
Autores principales: Hussan, Hisham, Zhao, Jing, Badu-Tawiah, Abraham K., Stanich, Peter, Tabung, Fred, Gray, Darrell, Ma, Qin, Kalady, Matthew, Clinton, Steven K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9064446/
https://www.ncbi.nlm.nih.gov/pubmed/35271664
http://dx.doi.org/10.1371/journal.pone.0265209

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9064446/
https://www.ncbi.nlm.nih.gov/pubmed/35271664
http://dx.doi.org/10.1371/journal.pone.0265209

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