Explainable Machine Learning Predictions for the Benefit From Chemotherapy in Advanced Non‐Small Cell Lung Cancer Without Available Targeted Mutations
By machine learning, we developed a predictive model to assess chemotherapy benefits in NSCLC patients without targeted mutations, utilizing eight readily available and non-invasive clinical indicators. Demonstrating satisfactory predictive performance and clinical practicability, this model may help clinicians identify patients' tendency to benefit from chemotherapy, potentially improving their prognosis.
Authors
- Yue Cheng (ORCID: https://orcid.org/0009-0007-7036-2129)
- Shuang Zhao (ORCID: https://orcid.org/0000-0001-9377-0124)
- Xiong Xingyu (ORCID: https://orcid.org/0000-0001-6021-1721)
- Yu Mingjing
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
Publication Details
- Journal
- The Clinical Respiratory Journal
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1111/crj.70044
- Citations
- 1
- Primary Topic
- Inflammatory Biomarkers in Disease Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 0.28
Funders
- Bethune Charitable Foundation
- Department of Science and Technology of Sichuan Province
- Natural Science Foundation of Sichuan Province