Unlocking The Potential of Hybrid Models for Prognostic Biomarker Discovery in Oral Cancer Survival Analysis: A Retrospective Cohort Study.
The PSO-based hybrid model effectively improved SVR performance in survival prediction for OC patients and identified key prognostic biomarkers. Despite its promising results and validation on independent datasets, limitations in generalizability and signs of overfitting suggest the model is not yet ready for clinical use. Further studies with larger, diverse datasets are recommended.
Authors
- Leili Tapak (ORCID: https://orcid.org/0000-0002-4378-3143)
- Anoshirvan Kazemnejad (ORCID: https://orcid.org/0000-0002-0143-9635)
- Linda Farahani (ORCID: https://orcid.org/0000-0001-7528-2979)
- Mahlagha Afrasiabi (ORCID: https://orcid.org/0000-0001-9472-4453)
Institutions
- Hamedan University of Medical Sciences (IR)
- Tarbiat Modares University (IR)
- Hamedan University of Technology (IR)
Publication Details
- Journal
- PubMed
- Published
- 2025-06-08
- DOI
- https://doi.org/10.22074/cellj.2025.2034704.1618
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00