Prediction of genomic biomarkers for endometriosis using the transcriptomic dataset
This study determined possible genomic biomarkers for endometriosis using transcriptomic data from patients with/without endometriosis. The applied ML model successfully classified endometriosis and created a highly accurate diagnostic prediction model. Future genomic studies could explain the underlying pathology of endometriosis, and a non-invasive diagnostic method could replace the invasive ones.
Authors
- Zeynep Kucukakcali
- Sami Akbulut (ORCID: https://orcid.org/0000-0002-6864-7711)
- Cemil Çolak (ORCID: https://orcid.org/0000-0001-5406-098X)
Institutions
- Inonu University (TR)
Publication Details
- Journal
- World Journal of Clinical Cases
- Published
- 2025-04-08
- DOI
- https://doi.org/10.12998/wjcc.v13.i20.104556
- Citations
- 2
- Primary Topic
- Endometriosis Research and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 3.40