Simultaneous Identification of <i>EGFR,</i><i>KRAS,</i><i>ERBB2,</i> and <i>TP53</i> Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics

Simultaneous Identification of <i>EGFR,</i><i>KRAS,</i><i>ERBB2,</i> and <i>TP53</i> Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics

Purpose: To develop a machine learning-derived radiomics approach to simultaneously discriminate epidermal growth factor receptor (<i>EGFR</i>), Kirsten rat sarcoma viral oncogene (<i>KRAS</i>), Erb-B2 receptor tyrosine kinase 2 (<i>ERBB2</i>), and tumor protein 5...

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Bibliographic Details
Main Authors: Tiening Zhang, Zhihan Xu, Guixue Liu, Beibei Jiang, Geertruida H. de Bock, Harry J. M. Groen, Rozemarijn Vliegenthart, Xueqian Xie
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Cancers
Subjects:
radiomics
next-generation sequencing (NGS)
non-small cell lung cancer (NSCLC)
screening
computed tomography
Online Access:https://www.mdpi.com/2072-6694/13/8/1814

Internet

https://www.mdpi.com/2072-6694/13/8/1814

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