Diagnostic performance of machine learning-based radiomics models for predicting epidermal growth factor receptor mutation status in lung adenocarcinoma in Chinese patients: A systematic review and meta-analysis.
- DOI
- 10.1177/03000605261460311
- Published
- 2026 Jul
- Container
- The Journal of international medical research
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1177/03000605261460311,
title = {Diagnostic performance of machine learning-based radiomics models for predicting epidermal growth factor receptor mutation status in lung adenocarcinoma in Chinese patients: A systematic review and meta-analysis.},
author = {Yang J and Jiang J and Peng J and Li J and Mi P and Chen G},
year = {2026},
journal = {The Journal of international medical research},
doi = {10.1177/03000605261460311},
url = {https://doi.org/10.1177/03000605261460311}
}RIS
TY - JOUR TI - Diagnostic performance of machine learning-based radiomics models for predicting epidermal growth factor receptor mutation status in lung adenocarcinoma in Chinese patients: A systematic review and meta-analysis. AU - Yang J AU - Jiang J AU - Peng J AU - Li J AU - Mi P AU - Chen G PY - 2026 JO - The Journal of international medical research DO - 10.1177/03000605261460311 UR - https://doi.org/10.1177/03000605261460311 ER -
APA
J, Y., J, J., J, P., J, L., P, M., & G, C. (2026). Diagnostic performance of machine learning-based radiomics models for predicting epidermal growth factor receptor mutation status in lung adenocarcinoma in Chinese patients: A systematic review and meta-analysis.. The Journal of international medical research. https://doi.org/10.1177/03000605261460311
Source records
- pubmed · retrieved 2026-09-26T18:52:34.207Z