Integrating machine learning with web-based tools for personalized prognosis in oral adenoid cystic carcinoma
This study contributes evidence and knowledge to the limited literature on ACC and emphasizes the importance of adjuvant radiotherapy. This study highlights that metastasis and age are key prognostic factors. Furthermore, the developed ML-based web tool offers a novel approach for the personalized prognosis of these rare cancer types.
Authors
- Mohammad Alkhatib (ORCID: https://orcid.org/0000-0003-0085-8990)
- Sakhr Alshwayyat (ORCID: https://orcid.org/0000-0002-2295-1945)
- Mustafa Alshwayyat
- Tala Abdulsalam Alshwayyat (ORCID: https://orcid.org/0009-0009-1754-2395)
- Hebah Almahariq
- Hamza Al Salieti
- Lina Khasawneh
Institutions
- University of Jordan (JO)
- Jordan University of Science and Technology (JO)
- King Hussein Cancer Center (JO)
- Jordan Hospital (JO)
- King Abdullah University Hospital (JO)
Publication Details
- Journal
- Journal of Stomatology Oral and Maxillofacial Surgery
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1016/j.jormas.2024.102143
- Citations
- 3
- Primary Topic
- Salivary Gland Tumors Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.72