A hybrid machine learning model combining association rule mining and classification algorithms to predict differentiated thyroid cancer recurrence
This study introduces a robust and interpretable predictive model that enhances personalized medicine in thyroid cancer care. The model effectively identifies high-risk individuals, allowing for tailored follow-up strategies that could improve patient outcomes and optimize resource allocation in DTC management.
Authors
- Nasrin Mansuri
- Emin Tamer Elkıran (ORCID: https://orcid.org/0000-0001-6681-7249)
- Cemil Çolak (ORCID: https://orcid.org/0000-0001-5406-098X)
- Fatma Hilal Yağın (ORCID: https://orcid.org/0000-0002-9848-7958)
- Fuzail Ahmad (ORCID: https://orcid.org/0000-0002-1189-2206)
- Luca Paolo Ardigò (ORCID: https://orcid.org/0000-0001-7677-5070)
- Feyza Firat Atay
Institutions
- Alfaisal University (SA)
- Inonu University (TR)
- NLA University College (NO)
- King Khalid University (SA)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2024-10-04
- DOI
- https://doi.org/10.3389/fmed.2024.1461372
- Citations
- 17
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 6.08
Funders
- King Khalid University