Cargando…
Prediction of EGFR Mutation Status in Non–Small Cell Lung Cancer Based on Ensemble Learning
Objectives: We aimed to identify whether ensemble learning can improve the performance of the epidermal growth factor receptor (EGFR) mutation status predicting model. Methods: We retrospectively collected 168 patients with non–small cell lung cancer (NSCLC), who underwent both computed tomography (...
Autores principales: | Feng, Youdan, Song, Fan, Zhang, Peng, Fan, Guangda, Zhang, Tianyi, Zhao, Xiangyu, Ma, Chenbin, Sun, Yangyang, Song, Xiao, Pu, Huangsheng, Liu, Fei, Zhang, Guanglei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271946/ https://www.ncbi.nlm.nih.gov/pubmed/35833032 http://dx.doi.org/10.3389/fphar.2022.897597 |
Ejemplares similares
-
In vivo accurate detection of the liver tumor with pharmacokinetic parametric images from dynamic fluorescence molecular tomography
por: Liu, Fei, et al.
Publicado: (2022) -
PET/CT Based EGFR Mutation Status Classification of NSCLC Using Deep Learning Features and Radiomics Features
por: Huang, Weicheng, et al.
Publicado: (2022) -
D2A U-Net: Automatic segmentation of COVID-19 CT slices based on dual attention and hybrid dilated convolution
por: Zhao, Xiangyu, et al.
Publicado: (2021) -
A Multi-Classification Model for Predicting the Invasiveness of Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodules
por: Song, Fan, et al.
Publicado: (2022) -
Cost-effectiveness of osimertinib versus standard EGFR-TKI as first-line treatment for EGFR-mutated advanced non-small-cell lung cancer in China
por: Shu, Yamin, et al.
Publicado: (2022)