Telomere Length Dynamics and Chromosomal Instability for Predicting Individual Radiosensitivity and Risk via Machine Learning

The ability to predict a cancer patient’s response to radiotherapy and risk of developing adverse late health effects would greatly improve personalized treatment regimens and individual outcomes. Telomeres represent a compelling biomarker of individual radiosensitivity and risk, as exposure can res...

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Detalles Bibliográficos
Autores principales: Luxton, Jared J., McKenna, Miles J., Lewis, Aidan M., Taylor, Lynn E., Jhavar, Sameer G., Swanson, Gregory P., Bailey, Susan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8002073/
https://www.ncbi.nlm.nih.gov/pubmed/33800260
http://dx.doi.org/10.3390/jpm11030188

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8002073/
https://www.ncbi.nlm.nih.gov/pubmed/33800260
http://dx.doi.org/10.3390/jpm11030188

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