Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis.

Lian Beenhakker Kim A E Wijlens Annemieke Witteveen Marianne J Heins Joke C Korevaar Kelly M de Ligt Christina Bode Miriam M R Vollenbroek-Hutten Sabine Siesling

Published in: Journal of cancer survivorship : research and practice (2023)

CRF is a common but underreported problem after breast cancer. We aimed to develop a model that could identify individuals with a high risk of developing CRF, ideally to help them prevent (chronic) CRF. As our models had poor predictive abilities, they cannot be used for this purpose yet. Adding patient-reported data as predictor could lead to improved results. Until then, awareness for CRF stays crucial.

Keyphrases

patient reported
machine learning
big data
electronic health record
artificial intelligence
sleep quality