Prediction of treatment (tx)-induced fatigue in breast cancer (BC) patients (pts) using machine learning on genome-wide association (GWAS) data in the prospective CANTO cohort.

Sangkyu Lee,Joseph O. Deasy,Jung Hun Oh,Antonio Di Meglio,Sandrine Boyault,Marina Rousseau-Tsangaris,Céline Besse,Emilie Thomas,Anne Boland-Auge,Paul Cottu,Olivier Tredan,Christelle Levy,Anne-Laure Martin,S Everhard,Patricia A. Ganz,Ann H. Partridge,Stefan Michiels,Jean-François Deleuze,Fabrice Andre,Ines Maria Vaz Duarte Luis

Prediction of treatment (tx)-induced fatigue in breast cancer (BC) patients (pts) using machine learning on genome-wide association (GWAS) data in the prospective CANTO cohort.

2019

11515Background: Many BC survivors report fatigue. The relevant genomic correlates of fatigue after BC are not well understood. We applied a previously validated machine learning methodology (Oh 20...

Keywords:

Canto
Artificial intelligence
Breast cancer
Machine learning
Cohort
Medicine
Genome-wide association study
gwas data

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