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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Radiomics evaluates the EGFR mutation status from the brain metastasis: a multi-center study
Ran Cao, Ziyan Pang, Xiaoyu Wang, et al.
Physics in Medicine and Biology (2022) Vol. 67, Iss. 12, pp. 125003-125003
Closed Access | Times Cited: 19

Showing 19 citing articles:

MRI-based habitat imaging in cancer treatment: current technology, applications, and challenges
Shaolei Li, Yongming Dai, Jiayi Chen, et al.
Cancer Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 8
A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer
Ye Li, Xinna Lv, Cancan Chen, et al.
European Radiology Experimental (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 6
MRI radiomics for brain metastasis sub-pathology classification from non-small cell lung cancer: a machine learning, multicenter study
Fuxing Deng, Zhiyuan Liu, Fang Wei, et al.
Physical and Engineering Sciences in Medicine (2023) Vol. 46, Iss. 3, pp. 1309-1320
Closed Access | Times Cited: 13
Development and external validation of an MRI-based neural network for brain metastasis segmentation in the AURORA multicenter study
Josef A. Buchner, Florian Kofler, Lucas Etzel, et al.
Radiotherapy and Oncology (2022) Vol. 178, pp. 109425-109425
Open Access | Times Cited: 21
Habitat‐based MRI radiomics to predict the origin of brain metastasis
Yiyao Sun, Yan Wang, Mingchen Jiang, et al.
Medical Physics (2025)
Closed Access
The potential of MRI radiomics based on extrapulmonary metastases in predicting EGFR mutations: a systematic review and meta-analysis
Linyong Wu, Dayou Wei, Songhua Li, et al.
BioMedical Engineering OnLine (2025) Vol. 24, Iss. 1
Open Access
A Bayesian meta-analysis on MRI-based radiomics for predicting EGFR mutation in brain metastasis of lung cancer
Peyman Tabnak, Zana Kargar, Mohammad Ebrahimnezhad, et al.
BMC Medical Imaging (2025) Vol. 25, Iss. 1
Open Access
Habitat radiomics assists radiologists in accurately diagnosing lymph node metastasis of adenocarcinoma of the esophagogastric junction
Pingfan Jia, Yueying Li, Haonan Li, et al.
Insights into Imaging (2025) Vol. 16, Iss. 1
Open Access
Machine learning in prediction of epidermal growth factor receptor status in non-small cell lung cancer brain metastases: a systematic review and meta-analysis
Bardia Hajikarimloo, Ibrahim Mohammadzadeh, Salem M. Tos, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
Open Access
Brain‐Tumor Interface‐Based MRI Radiomics Models to Determine EGFR Mutation, Response to EGFR‐TKI and T790M Resistance Mutation in Non‐Small Cell Lung Carcinoma Brain Metastasis
Ying Fan, Xinti Wang, Chunna Yang, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 58, Iss. 6, pp. 1838-1847
Closed Access | Times Cited: 8
Brain metastasis magnetic resonance imaging-based deep learning for predicting epidermal growth factor receptor (EGFR) mutation and subtypes in metastatic non-small cell lung cancer
Ran Cao, Langyuan Fu, Bo Huang, et al.
Quantitative Imaging in Medicine and Surgery (2024) Vol. 14, Iss. 7, pp. 4749-4762
Open Access | Times Cited: 1
Predicting the T790M mutation in non-small cell lung cancer (NSCLC) using brain metastasis MR radiomics: a study with an imbalanced dataset
Wen-Feng Wu, Kuan-Ming Lai, Chia‐Hung Chen, et al.
Discover Oncology (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Comprehensive analysis of prediction of the EGFR mutation and subtypes based on the spinal metastasis from primary lung adenocarcinoma
Ran Cao, Huanhuan Chen, Huan Wang, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 3
Universal multi-factor feature selection method for radiomics-based brain tumor classification
Longfei Li, Meiyun Wang, Xiaoming Jiang, et al.
Computers in Biology and Medicine (2023) Vol. 164, pp. 107122-107122
Closed Access | Times Cited: 3
Discordant and Converting Receptor Expressions in Brain Metastases from Breast Cancer: MRI-Based Non-Invasive Receptor Status Tracking
Alexander Heitkamp, Frederic Madesta, Sophia Amberg, et al.
Cancers (2023) Vol. 15, Iss. 11, pp. 2880-2880
Open Access | Times Cited: 2
Radiomic signatures for the non-invasive prediction of EGFR mutation status in brain metastases of lung adenocarcinoma
Liheng Yu, Linlin Sun, Li Zhu, et al.
Research Square (Research Square) (2024)
Open Access
Habitat-Based Radiomics for Predicting EGFR Mutations in Exon 19 and 21 From Brain Metastasis
Chunna Yang, Ying Fan, Dan Zhao, et al.
Academic Radiology (2024) Vol. 31, Iss. 9, pp. 3764-3773
Closed Access
Habitat-Based MRI Radiomics to Predict the Origin of Brain Metastasis
Yiyao Sun, Peng Zhao, Mingchen Jiang, et al.
(2024)
Closed Access
Predictive Modeling of Brain Metastasis in Advanced Lung Adenocarcinoma: A Hybrid Approach Combining Traditional Radiomics and Deep Learning from Thoracic CT Images
Shuai Qie, Larry E. Kun, Hongyun Shi, et al.
Research Square (Research Square) (2024)
Open Access
Tumor‐liver interface in MRI of liver metastasis enables prediction of EGFR mutation in patients with lung cancer: A proof‐of‐concept study
Shaoping Hou, Hongbo Wang, Xiaoyu Wang, et al.
Medical Physics (2023) Vol. 51, Iss. 2, pp. 1083-1091
Closed Access | Times Cited: 1
Multisequence MRI-based radiomics analysis for early prediction of the risk of T790M resistance in new brain metastases
Xinna Lv, Ye Li, Bing Wang, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 13, Iss. 12, pp. 8599-8610
Open Access | Times Cited: 1
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