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:

Predicting Survival Duration With MRI Radiomics of Brain Metastases From Non-small Cell Lung Cancer
Bihong T. Chen, Taihao Jin, Ningrong Ye, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Integration of artificial intelligence in lung cancer: Rise of the machine
Colton Ladbury, Arya Amini, Ameish Govindarajan, et al.
Cell Reports Medicine (2023) Vol. 4, Iss. 2, pp. 100933-100933
Open Access | Times Cited: 44

Radiogenomics: a key component of precision cancer medicine
Zaoqu Liu, Tian Duan, Yuyuan Zhang, et al.
British Journal of Cancer (2023) Vol. 129, Iss. 5, pp. 741-753
Open Access | Times Cited: 43

Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future
Michaela Cellina, Maurizio Cè, Giovanni Irmici, et al.
Diagnostics (2022) Vol. 12, Iss. 11, pp. 2644-2644
Open Access | Times Cited: 48

Precision oncology provides opportunities for targeting KRAS-inhibitor resistance
Martin Sattler, Atish Mohanty, Prakash Kulkarni, et al.
Trends in cancer (2022) Vol. 9, Iss. 1, pp. 42-54
Open Access | Times Cited: 28

Radiological artificial intelligence - predicting personalized immunotherapy outcomes in lung cancer
Laila C. Roisman, Waleed Kian, Alaa Anoze, et al.
npj Precision Oncology (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 19

Review of Current Principles of the Diagnosis and Management of Brain Metastases
Alex W. Brenner, Akash J. Patel
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 26

Application of radiomics in diagnosis and treatment of lung cancer
Feng Pan, Feng Li, Baocai Liu, et al.
Frontiers in Pharmacology (2023) Vol. 14
Open Access | Times Cited: 16

Multiregional radiomics of brain metastasis can predict response to EGFR-TKI in metastatic NSCLC
Ying Fan, Xinti Wang, Yue Dong, et al.
European Radiology (2023) Vol. 33, Iss. 11, pp. 7902-7912
Closed Access | Times Cited: 13

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

Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers
Pankaj Garg, Atish Mohanty, Sravani Ramisetty, et al.
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer (2023) Vol. 1878, Iss. 6, pp. 189026-189026
Open Access | Times Cited: 12

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

A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer
Serafeim‐Chrysovalantis Kotoulas, Dionysios Spyratos, Κonstantinos Porpodis, et al.
Cancers (2025) Vol. 17, Iss. 5, pp. 882-882
Open Access

Preoperative MRI‐Based Radiomics of Brain Metastasis to Assess T790M Resistance Mutation After EGFR‐TKI Treatment in NSCLC
Ying Fan, Lingzi He, Huazhe Yang, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 57, Iss. 6, pp. 1778-1787
Closed Access | Times Cited: 17

Development and externally validate MRI-based nomogram to assess EGFR and T790M mutations in patients with metastatic lung adenocarcinoma
Ying Fan, Yue Dong, Huan Wang, et al.
European Radiology (2022) Vol. 32, Iss. 10, pp. 6739-6751
Closed Access | Times Cited: 16

Artificial Intelligence for Survival Prediction in Brain Tumors on Neuroimaging
Anne Jian, Sidong Liu, Antonio Di Ieva
Neurosurgery (2022) Vol. 91, Iss. 1, pp. 8-26
Closed Access | Times Cited: 15

Radiomics as an emerging tool in the management of brain metastases
Alexander Nowakowski, Zubin Lahijanian, Valérie Panet-Raymond, et al.
Neuro-Oncology Advances (2022) Vol. 4, Iss. 1
Open Access | Times Cited: 14

Differentiating Glioblastoma Multiforme from Brain Metastases Using Multidimensional Radiomics Features Derived from MRI and Multiple Machine Learning Models
Salar Bijari, Amin Jahanbakhshi, Parham Hajishafiezahramini, et al.
BioMed Research International (2022) Vol. 2022, pp. 1-10
Open Access | Times Cited: 13

Targeting CNS Metastases in Non–Small Cell Lung Cancer With Evolving Approaches Using Molecular Markers
Jyoti Malhotra, Isa Mambetsariev, Gregory Gilmore, et al.
JAMA Oncology (2024)
Closed Access | Times Cited: 2

Imaging of brain metastasis in non-small-cell lung cancer: indications, protocols, diagnosis, post-therapy imaging, and implications regarding management
Nivedita Chakrabarty, Abhishek Mahajan, Vasundhara Patil, et al.
Clinical Radiology (2022) Vol. 78, Iss. 3, pp. 175-186
Closed Access | Times Cited: 10

Artificial Intelligence in Lung Cancer Imaging: From Data to Therapy
Michaela Cellina, Giuseppe De Padova, Nazarena Caldarelli, et al.
Critical Reviews™ in Oncogenesis (2023) Vol. 29, Iss. 2, pp. 1-13
Closed Access | Times Cited: 6

Elaboration of Multiparametric MRI‐Based Radiomics Signature for the Preoperative Quantitative Identification of the Histological Grade in Patients With Non‐Small‐Cell Lung Cancer
Xing Tang, Guoyan Bai, Hong Wang, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 56, Iss. 2, pp. 579-589
Closed Access | Times Cited: 9

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