Personalized Risk Analysis to Improve the Psychological Resilience of Women Undergoing Treatment for Breast Cancer: Development of a Machine Learning-Driven Clinical Decision Support Tool.
Georgios C ManikisNicholas John SimosKonstantina D KourouHaridimos KondylakisPaula Poikonen-SakselaKetti MazzoccoRuth Pat-HorenczykBerta SousaAlbino J Oliveira-MaiaJohanna MattsonIlan RozinerChiara MarzoratiKonstantinos MariasMikko NuutinenEvangelos C KarademasDimitrios Ioannis FotiadisPublished in: Journal of medical Internet research (2023)
Our results highlight the clinical utility of the BOUNCE modeling approach by focusing on resilience predictors that can be readily available to practicing clinicians at major oncology centers. The BOUNCE CDS tool paves the way for personalized risk assessment methods to identify patients at high risk of adverse well-being outcomes and direct valuable resources toward those most in need of specialized psychological interventions.
Keyphrases
- clinical decision support
- palliative care
- machine learning
- risk assessment
- climate change
- electronic health record
- social support
- breast cancer risk
- polycystic ovary syndrome
- physical activity
- quantum dots
- sleep quality
- artificial intelligence
- pregnancy outcomes
- big data
- young adults
- deep learning
- insulin resistance
- skeletal muscle
- patient reported
- visible light