Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data
This study innovatively developed a predictive model for benign and malignant TNs based on the Gradient Boosting Decision Tree algorithm. For the first time, it validated the clinical predictive value of TF parameters (FT4, FT3) and TPOAB as key biomarkers.
Authors
- Ma Fuqiang (ORCID: https://orcid.org/0000-0002-7792-7432)
- Fengchang Yu (ORCID: https://orcid.org/0000-0002-6503-4688)
- He-Rong Mao
- Lihua Zhang (ORCID: https://orcid.org/0000-0003-4965-5131)
- Lele Zhang (ORCID: https://orcid.org/0009-0007-1331-5086)
- Quan Zhou (ORCID: https://orcid.org/0000-0002-9428-175X)
- Nan Xiang (ORCID: https://orcid.org/0000-0003-0347-1580)
- Shenhui Lv
- Zhilin Lu
Institutions
- Hubei University of Chinese Medicine (CN)
- Wuhan University (CN)
- Hubei Provincial Hospital of Traditional Chinese Medicine (CN)
- Hubei University Of Economics (CN)
- First Affiliated Hospital of Henan University of Science and Technology (CN)
- Huanggang Central Hospital (CN)
Publication Details
- Journal
- BMJ Open
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1136/bmjopen-2024-093466
- Citations
- 3
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 3.88