A Machine Learning Classification Model for Gastrointestinal Health in Cancer Survivors: Roles of Telomere Length and Social Determinants of Health
Our findings provide valuable insights into classifying and identifying risk factors related to GI health, including biological aging and SDOH indicators. To enhance model predictability, further longitudinal studies and external clinical validations are necessary.
Authors
- Christin E. Burd (ORCID: https://orcid.org/0000-0002-7919-3954)
- Anne M. Noonan (ORCID: https://orcid.org/0000-0001-8083-8492)
- Xia Ning (ORCID: https://orcid.org/0000-0002-6842-1165)
- Diane Von Ah (ORCID: https://orcid.org/0000-0002-3189-1307)
- Fode Tounkara (ORCID: https://orcid.org/0009-0004-4756-5903)
- Claire J. Han (ORCID: https://orcid.org/0000-0001-6081-3378)
- Matthew F. Kalady (ORCID: https://orcid.org/0000-0002-2114-114X)
Institutions
- The Ohio State University Comprehensive Cancer Center – Arthur G. James Cancer Hospital and Richard J. Solove Research Institute (US)
- Cancer Genetics (United States) (US)
- The Ohio State University (US)
Publication Details
- Journal
- International Journal of Environmental Research and Public Health
- Published
- 2024-12-19
- DOI
- https://doi.org/10.3390/ijerph21121694
- Primary Topic
- Nutritional Studies and Diet
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Brown University