Well-being trajectories in breast cancer and their predictors: A machine-learning approach.
Evangelos C KarademasEugenia MylonaKetti MazzoccoRuth Pat-HorenczykBerta SousaAlbino J Oliveira-MaiaJose OliveiraIlan RozinerGeorgios StamatakosFatima CardosoHaridimos KondylakisEleni KolokotroniKonstantina KourouRaquel LemosIsabel ManicaGeorge ManikisChiara MarzoratiJohanna MattsonLuzia TravadoChariklia Tziraki-SegalDimitris FotiadisPaula Poikonen-SakselaPanagiotis Simosnull nullPublished in: Psycho-oncology (2023)
There is a strong possibility that resilience does not always reflect a stable response pattern, as there might be some interim fluctuations. The use of machine-learning techniques provides a unique opportunity for the identification of illness trajectories and a shortlist of major bio/behavioral predictors. This will facilitate the development of early interventions to prevent a significant deterioration in patient well-being.