Machine-learning diagnostics of breast cancer using piRNA biomarkers
Our study demonstrates the effectiveness of using ML-based piRNA classifiers in diagnosing breast cancer and contributes to the growing body of evidence supporting piRNAs as biomarkers in cancer diagnosis. However, additional research is needed to validate these findings and further assess the clinical applicability of this approach.
Authors
- Alison Zhao (ORCID: https://orcid.org/0000-0002-5479-2686)
- Igor F. Tsigelny (ORCID: https://orcid.org/0000-0002-7155-8947)
- Valentina L. Kouznetsova (ORCID: https://orcid.org/0000-0001-9457-7027)
- Santosh Kesari (ORCID: https://orcid.org/0000-0003-3772-6000)
Institutions
- San Diego Supercomputer Center (US)
- University of California San Diego (US)
- Neuroscience Institute (IT)
- Centro Universitário do Espírito Santo (BR)
- Environmental Research Institute (GB)
Publication Details
- Journal
- Biomarkers
- Published
- 2025-02-03
- DOI
- https://doi.org/10.1080/1354750x.2025.2461067
- Citations
- 3
- Primary Topic
- MicroRNA in disease regulation
- Type
- article
- Field-Weighted Citation Impact
- 2.81