A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

doi:10.1016/j.acra.2023.06.026

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A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

Academic radiology - 1 Feb 2024

Zheng Ying-Mei, Pang Jing, Liu Zong-Jing, Yuan Ming-Gang, Li Jie, Wu Zeng-Jie, Jiang Yan, Dong Cheng

Abstract excerpt

RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation status in head and neck squamous cell carcinoma (HNSCC) patients is crucial for prognosis and treatment selection. This study aimed to construct and validate a contrast-enhanced computed tomography (CECT)-based deep learning radiomics nomogram (DLRN) to predict EGFR mutation status of HNSCC. MATERIALS AND METHODS: A...

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PMID: 37481418
DOI: 10.1016/j.acra.2023.06.026

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