A machine learning-based prediction of the micropapillary/solid growth pattern in invasive lung adenocarcinoma with radiomics
Author:
Publisher
AME Publishing Company
Subject
Oncology
Link
https://tlcr.amegroups.com/article/download/49585/pdf
Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma;Insights into Imaging;2024-01-08
2. Predicting micropapillary or solid pattern of lung adenocarcinoma with CT-based radiomics, conventional radiographic and clinical features;Respiratory Research;2023-11-14
3. Feasibility of UTE-MRI-based radiomics model for prediction of histopathologic subtype of lung adenocarcinoma: in comparison with CT-based radiomics model;European Radiology;2023-10-16
4. Integrated Multi-omics Analysis of Early Lung Adenocarcinoma Links Tumor Biological Features with Predicted Indolence or Aggressiveness;Cancer Research Communications;2023-07-26
5. Review of the use of radiomics to assess the risk of recurrence in early-stage non-small cell lung cancer;Translational Lung Cancer Research;2023-07
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