Prediction of recurrence-free survival and risk factors of sinonasal inverted papilloma after surgery by machine learning models
To our knowledge, this is the first study to use multiple ML models to predict postoperative recurrence of IP. The EST model has the best predictive performance, with SHAP emphasizing several key predictive factors for IP recurrence. This study emphasizes the practicality of machine learning algorithms in predicting IP clinical outcomes, providing valuable insights into the potential for improving clinical decision-making.
Authors
- Xiaodong Chen (ORCID: https://orcid.org/0000-0002-5839-7886)
- Yaqi Li (ORCID: https://orcid.org/0009-0002-9946-7390)
- Siyu Miao (ORCID: https://orcid.org/0000-0003-0464-1457)
- Dingjun Zha (ORCID: https://orcid.org/0000-0002-9380-9209)
- Tao Xue (ORCID: https://orcid.org/0000-0003-1047-4966)
- Fuquan Chen (ORCID: https://orcid.org/0000-0002-4625-073X)
- Cheng Yang
Institutions
- Xi'an Railway Survey and Design Institute (CN)
- Xijing Hospital (CN)
- Air Force Medical University (CN)
Publication Details
- Journal
- European journal of medical research
- Published
- 2024-11-04
- DOI
- https://doi.org/10.1186/s40001-024-02099-6
- Citations
- 5
- Primary Topic
- Head and Neck Surgical Oncology
- Type
- article
- Field-Weighted Citation Impact
- 2.86