Predicting EGFR Mutation Status in Non–Small Cell Lung Cancer Using Artificial Intelligence: A Systematic Review and Meta-Analysis-Reference-Cited by-同舟云学术

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Predicting EGFR Mutation Status in Non–Small Cell Lung Cancer Using Artificial Intelligence: A Systematic Review and Meta-Analysis

Published:2023-04 Issue: Volume: Page:
ISSN:1076-6332
Container-title:Academic Radiology
language:en
Short-container-title:Academic Radiology

Author:

Nguyen Hung Song,Ho Dang Khanh Ngan,Nguyen Nam Nhat,Tran Huy Minh,Tam Ka-Wai,Le Nguyen Quoc Khanh

Funder

Ministry of Science and Technology, Taiwan

Ministry of Education

National Science and Technology Council

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging

Reference67 articles.

1. Global epidemiology of lung cancer;Barta;Ann Glob Health,2019

2. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries;Sung;CA Cancer J Clin,2021

3. EGFR mutation testing in lung cancer: a review of available methods and their use for analysis of tumour tissue and cytology samples;Ellison;J Clin Pathol,2013

4. The role of positron emission tomography in the diagnosis, staging and response assessment of non-small cell lung cancer;Volpi;Ann Transl Med,2018

5. Artificial intelligence in cancer research and precision medicine;Bhinder;Cancer Discov,2021

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3. Diagnostic accuracy of CT and PET/CT radiomics in predicting lymph node metastasis in non-small cell lung cancer;European Radiology;2024-09-02

4. Leveraging multi-omics and machine learning approaches in malting barley research: From farm cultivation to the final products;Current Plant Biology;2024-09

5. Comprehensive Potential of Artificial Intelligence for Predicting PD-L1 Expression and EGFR Mutations in Lung Cancer: A Systematic Review and Meta-Analysis;Journal of Computer Assisted Tomography;2024-08-12

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