Prediction model based on 18F-FDG PET/CT radiomic features and clinical factors of EGFR mutations in lung adenocarcinoma

Volume: 69, Issue: 01, Pages: 233 - 241
Published: Jan 1, 2022
Abstract
The aim of this study was to build a prediction model for epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma. A retrospective analysis was performed on 88 patients with lung adenocarcinoma. All patients underwent an 18F-FDG PET/CT scan and genetic testing of EGFR before the treatment. In the training set, the radiomic features and clinical factors were screened out, and model-1 based on CT radiomic features, model-2 based...
Paper Details
Title
Prediction model based on 18F-FDG PET/CT radiomic features and clinical factors of EGFR mutations in lung adenocarcinoma
Published Date
Jan 1, 2022
Journal
Volume
69
Issue
01
Pages
233 - 241
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.