Machine Learning–Based Prediction of Clinical Outcomes in Patients With Cancer Receiving Systemic Treatment Using Step Count Data Measured With Smartphones
A decline in daily step counts can serve as an early predictor for hospitalizations in the upcoming 7 days, facilitating proactive and preventive toxicity management strategies.
Authors
- Joeri A J Douma (ORCID: https://orcid.org/0000-0003-4433-0370)
- Evelien J. M. Kuip (ORCID: https://orcid.org/0000-0002-9114-643X)
- Laurien M. Buffart (ORCID: https://orcid.org/0000-0002-8095-436X)
- Calvin G. Brouwer (ORCID: https://orcid.org/0000-0003-0729-6011)
- Leni van Doorn (ORCID: https://orcid.org/0000-0002-2494-4482)
- Henk M.W. Verheul (ORCID: https://orcid.org/0000-0001-5981-922X)
- Branca M. Bartelet
Institutions
- Radboud University Nijmegen (NL)
- Medisch Centrum Leeuwarden (NL)
- Radboud University Medical Center (NL)
- Erasmus MC Cancer Institute (NL)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2025-06-30
- DOI
- https://doi.org/10.1200/cci-25-00023
- Citations
- 2
- Primary Topic
- Cancer survivorship and care
- Type
- article
- Field-Weighted Citation Impact
- 2.09