Cargando…
Three-Dimensional Convolutional Neural Network-Based Prediction of Epidermal Growth Factor Receptor Expression Status in Patients With Non-Small Cell Lung Cancer
OBJECTIVES: EGFR testing is a mandatory step before targeted therapy for non-small cell lung cancer patients. Combining some quantifiable features to establish a predictive model of EGFR expression status, break the limitations of tissue biopsy. MATERIALS AND METHODS: We retrospectively analyzed 107...
Autores principales: | Huang, Xuemei, Sun, Yingli, Tan, Mingyu, Ma, Weiling, Gao, Pan, Qi, Lin, Lu, Jinjuan, Yang, Yuling, Wang, Kun, Chen, Wufei, Jin, Liang, Kuang, Kaiming, Duan, Shaofeng, Li, Ming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848731/ https://www.ncbi.nlm.nih.gov/pubmed/35186727 http://dx.doi.org/10.3389/fonc.2022.772770 |
Ejemplares similares
-
Prediction of the Growth Rate of Early-Stage Lung Adenocarcinoma by Radiomics
por: Tan, Mingyu, et al.
Publicado: (2021) -
A Computed Tomography-Derived Radiomics Approach for Predicting Uncommon EGFR Mutation in Patients With NSCLC
por: Chen, Wufei, et al.
Publicado: (2021) -
The Potential of Radiomics Nomogram in Non-invasively Prediction of Epidermal Growth Factor Receptor Mutation Status and Subtypes in Lung Adenocarcinoma
por: Zhao, Wei, et al.
Publicado: (2020) -
Dose Prediction Using a Three-Dimensional Convolutional Neural Network for Nasopharyngeal Carcinoma With Tomotherapy
por: Liu, Yaoying, et al.
Publicado: (2021) -
Bioluminescence Tomography Based on One-Dimensional Convolutional Neural Networks
por: Yu, Jingjing, et al.
Publicado: (2021)