Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Papillary Thyroid Carcinoma Variants
This study offers a comprehensive approach for treating and assessing prognosis in PTC variants. The ML models developed offer practical tools for personalized clinical decision-making.
Authors
- Hamdah Hanifa (ORCID: https://orcid.org/0000-0003-2970-7379)
- Owais Ghammaz (ORCID: https://orcid.org/0009-0004-8914-6483)
- Wafa Asha (ORCID: https://orcid.org/0000-0002-1046-770X)
- Nesreen Saadeh (ORCID: https://orcid.org/0000-0003-1666-6854)
- Sakhr Alshwayyat (ORCID: https://orcid.org/0000-0002-2295-1945)
- Mustafa Alshwayyat
- Tala Abdulsalam Alshwayyat (ORCID: https://orcid.org/0009-0009-1754-2395)
- Ramez M. Odat (ORCID: https://orcid.org/0009-0008-3423-4055)
- Haya Kamal (ORCID: https://orcid.org/0000-0001-9317-2044)
Institutions
- Applied Science Private University (JO)
- Jordan University of Science and Technology (JO)
- King Hussein Cancer Center (JO)
- University of Kalamoon (SY)
- Médecins Sans Frontières (JO)
Publication Details
- Journal
- Cancer Reports
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1002/cnr2.70071
- Citations
- 3
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.07