Decoding ancestry-specific genetic risk: interpretable deep feature selection reveals prostate cancer SNP disparities in diverse populations
By synergizing interpretable feature selection with deep learning, this work advances the translation of SNP-based biomarkers into clinically actionable tools while clarifying their contested diagnostic role in PCa.
Authors
- Andrea Edwards (ORCID: https://orcid.org/0000-0001-9780-7908)
- Zhaobai Lao
- You Lü (ORCID: https://orcid.org/0000-0002-6815-6568)
- Kun Zhang (ORCID: https://orcid.org/0009-0006-7907-4222)
- Wensheng Zhang (ORCID: https://orcid.org/0000-0002-6411-7801)
- Zhong Chen (ORCID: https://orcid.org/0000-0002-7483-9699)
Institutions
- Southern Illinois University Carbondale (US)
- Tulane University (US)
- Xavier University of Louisiana (US)
- University of Pennsylvania (US)
- Philadelphia University (US)
Publication Details
- Journal
- BioData Mining
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1186/s13040-025-00470-9
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health