Benchmarking machine learning approaches to predict radiation-induced toxicities in lung cancer patients

BACKGROUND AND PURPOSE: Radiation-induced toxicities are common adverse events in lung cancer (LC) patients undergoing radiotherapy (RT). An accurate prediction of these adverse events might facilitate an informed and shared decision-making process between patient and radiation oncologist with a cle...

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Detalles Bibliográficos
Autores principales: Núñez-Benjumea, Francisco J., González-García, Sara, Moreno-Conde, Alberto, Riquelme-Santos, José C., López-Guerra, José L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213176/
https://www.ncbi.nlm.nih.gov/pubmed/37251617
http://dx.doi.org/10.1016/j.ctro.2023.100640

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213176/
https://www.ncbi.nlm.nih.gov/pubmed/37251617
http://dx.doi.org/10.1016/j.ctro.2023.100640

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