Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography

PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely to benefit. We hypothesized that a deep learning mo...

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Detalles Bibliográficos
Autores principales: Mikhael, Peter G., Wohlwend, Jeremy, Yala, Adam, Karstens, Ludvig, Xiang, Justin, Takigami, Angelo K., Bourgouin, Patrick P., Chan, PuiYee, Mrah, Sofiane, Amayri, Wael, Juan, Yu-Hsiang, Yang, Cheng-Ta, Wan, Yung-Liang, Lin, Gigin, Sequist, Lecia V., Fintelmann, Florian J., Barzilay, Regina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2023
Materias:
ORIGINAL REPORTS
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419602/
https://www.ncbi.nlm.nih.gov/pubmed/36634294
http://dx.doi.org/10.1200/JCO.22.01345

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419602/
https://www.ncbi.nlm.nih.gov/pubmed/36634294
http://dx.doi.org/10.1200/JCO.22.01345

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