An optimization framework to guide the choice of thresholds for risk-based cancer screening

It is uncommon for risk groups defined by statistical or artificial intelligence (AI) models to be chosen by jointly considering model performance and potential interventions available. We develop a framework to rapidly guide choice of risk groups in this manner, and apply it to guide breast cancer...

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Detalles Bibliográficos
Autores principales: Brentnall, Adam R., Atakpa, Emma C., Hill, Harry, Santeramo, Ruggiero, Damiani, Celeste, Cuzick, Jack, Montana, Giovanni, Duffy, Stephen W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684532/
https://www.ncbi.nlm.nih.gov/pubmed/38017184
http://dx.doi.org/10.1038/s41746-023-00967-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684532/
https://www.ncbi.nlm.nih.gov/pubmed/38017184
http://dx.doi.org/10.1038/s41746-023-00967-9

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