Computed tomography‐based radiomics and clinical‐genetic features for brain metastasis prediction in patients with stage <scp>III</scp>/<scp>IV</scp> epidermal growth factor receptor‐mutant non‐small‐cell lung cancer

The combined radiomics-genetic model could be used to predict BM-FS in stage III/IV NSCLC patients with EGFR mutations.

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Publication Details

Journal
Thoracic Cancer
Published
2024-08-05
DOI
https://doi.org/10.1111/1759-7714.15410
Citations
6
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
2.43

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article

Computed tomography‐based radiomics and clinical‐genetic features for brain metastasis prediction in patients with stage III/IV epidermal growth factor receptor‐mutant non‐small‐cell lung cancer

Ligang Xing, Haoran Qi, Mingzhu Zhang, Xiaorong Sun et al.
6 citations
Thoracic Cancer
Radiomics and Machine Learning in Medical Imaging
2.43
article

Computed tomography‐based radiomics and clinical‐genetic features for brain metastasis prediction in patients with stage III/IV epidermal growth factor receptor‐mutant non‐small‐cell lung cancer

Ligang Xing, Haoran Qi, Mingzhu Zhang, Xiaorong Sun, Mei Zheng
article en
6 citations

Abstract

The combined radiomics-genetic model could be used to predict BM-FS in stage III/IV NSCLC patients with EGFR mutations.

Thoracic CancerVol. 15(27)
Shandong University (CN), Shandong Tumor Hospital (CN), Shandong First Medical University (CN)
Department of Science and Technology of Shandong Province, National Natural Science Foundation of China, Natural Science Foundation of Shandong Province
Reduced inequalities
Openalex Percentile: Top 11%
Radiomics and Machine Learning in Medical Imaging
2.43
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