Development and Validation of Machine Learning Models for Predicting Tumor Progression in <scp>OSCC</scp>
This study demonstrated ML models can improve clinical prediction of oral squamous cell carcinoma progression through basic information of patients. These tools could be used to provide individual risk estimation and may help direct intervention.
Authors
- Wei Deng (ORCID: https://orcid.org/0000-0001-8693-5322)
- Xueying Mei (ORCID: https://orcid.org/0000-0001-6564-7815)
- Xiaomei Lao (ORCID: https://orcid.org/0000-0001-5767-1823)
- Wan Duan (ORCID: https://orcid.org/0000-0002-8387-4170)
- Le Yang (ORCID: https://orcid.org/0000-0001-5309-7123)
- Sien Zhang
- Yujie Liang (ORCID: https://orcid.org/0000-0002-8658-4304)
- Jianbin Gong (ORCID: https://orcid.org/0000-0003-1716-336X)
- Guiqing Liao (ORCID: https://orcid.org/0000-0002-0338-6661)
- Wenhao Luo (ORCID: https://orcid.org/0000-0003-3481-8698)
- Bin Zeng
- Zhu-Ming Guo
Institutions
- Sun Yat-sen University (CN)
- Stomatology Hospital (CN)
- Sun Yat-sen University Cancer Center (CN)
- Hospital of Stomatology, Sun Yat-sen University
Publication Details
- Journal
- Oral Diseases
- Published
- 2024-10-27
- DOI
- https://doi.org/10.1111/odi.15159
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.81