Optimizing thyroid AUS nodules malignancy prediction: a comprehensive study of logistic regression and machine learning models
The LR model developed using the backward stepwise regression, outperformed ML models in predicting malignancy in AUS thyroid nodules. The corresponding nomogram based on this model provides a valuable and practical tool for personalized risk assessment, potentially reducing unnecessary surgeries and enhancing clinical decision-making.
Authors
- Mengqi Luan
- Yixian Yang (ORCID: https://orcid.org/0000-0001-8067-4774)
- Lu Zhang (ORCID: https://orcid.org/0000-0002-5078-972X)
- Yuan Cao (ORCID: https://orcid.org/0000-0001-6557-6519)
- Weiwei Zhan (ORCID: https://orcid.org/0000-0002-2509-5398)
- Wei Zhou (ORCID: https://orcid.org/0000-0002-9610-3113)
- Yan Hu
- Yunchao Chen
Institutions
- Shanghai Jiao Tong University (CN)
- Fudan University (CN)
- Ruijin Hospital (CN)
- Zhongshan Hospital of Xiamen University (CN)
Publication Details
- Journal
- Frontiers in Endocrinology
- Published
- 2024-11-06
- DOI
- https://doi.org/10.3389/fendo.2024.1366687
- Citations
- 5
- Primary Topic
- Thyroid Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.79
Funders
- National Natural Science Foundation of China