Machine Learning Identifies Clinical and Genetic Factors Associated With Anthracycline Cardiotoxicity in Pediatric Cancer Survivors

BACKGROUND: Despite known clinical risk factors, predicting anthracycline cardiotoxicity remains challenging. OBJECTIVES: This study sought to develop a clinical and genetic risk prediction model for anthracycline cardiotoxicity in childhood cancer survivors. METHODS: We performed exome sequencing i...

Descripción completa

Detalles Bibliográficos
Autores principales: Chaix, Marie-A, Parmar, Neha, Kinnear, Caroline, Lafreniere-Roula, Myriam, Akinrinade, Oyediran, Yao, Roderick, Miron, Anastasia, Lam, Emily, Meng, Guoliang, Christie, Anne, Manickaraj, Ashok Kumar, Marjerrison, Stacey, Dillenburg, Rejane, Bassal, Mylène, Lougheed, Jane, Zelcer, Shayna, Rosenberg, Herschel, Hodgson, David, Sender, Leonard, Kantor, Paul, Manlhiot, Cedric, Ellis, James, Mertens, Luc, Nathan, Paul C., Mital, Seema
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8352204/
https://www.ncbi.nlm.nih.gov/pubmed/34396283
http://dx.doi.org/10.1016/j.jaccao.2020.11.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8352204/
https://www.ncbi.nlm.nih.gov/pubmed/34396283
http://dx.doi.org/10.1016/j.jaccao.2020.11.004

Ejemplares similares