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

Luxton, Jared J; McKenna, Miles J; Lewis, Aidan M; Taylor, Lynn E; Jhavar, Sameer G; Swanson, Gregory P; Bailey, Susan M

Luxton, Jared J; McKenna, Miles J; Lewis, Aidan M; Taylor, Lynn E; Jhavar, Sameer G; Swanson, Gregory P; Bailey, Susan M.

Afiliación

Luxton JJ; Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA.
McKenna MJ; Cell and Molecular Biology Program, Colorado State University, Fort Collins, CO 80523, USA.
Lewis AM; Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA.
Taylor LE; Cell and Molecular Biology Program, Colorado State University, Fort Collins, CO 80523, USA.
Jhavar SG; Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA.
Swanson GP; Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, USA.
Bailey SM; Baylor Scott & White Medical Center, Temple, TX 76508, USA.

J Pers Med ; 11(3)2021 Mar 08.

Article en En | MEDLINE | ID: mdl-33800260

Palabras clave

IMRT; chromosomal instability; individual radiosensitivity; inversions; late effects; machine learning; personalized medicine; prostate cancer; telomeres

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Pers Med Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

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