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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:

Stage-Specific PET Radiomic Prediction Model for the Histological Subtype Classification of Non-Small-Cell Lung Cancer
Yanlei Ji, Qingtao Qiu, Jing Fu, et al.
Cancer Management and Research (2021) Vol. Volume 13, pp. 307-317
Open Access | Times Cited: 15

Showing 15 citing articles:

Challenges and limitations in applying radiomics to PET imaging: Possible opportunities and avenues for research
Alessandro Stefano
Computers in Biology and Medicine (2024) Vol. 179, pp. 108827-108827
Open Access | Times Cited: 16
[18F]FDG-PET/CT Radiomics and Artificial Intelligence in Lung Cancer: Technical Aspects and Potential Clinical Applications
Reyhaneh Manafi‐Farid, Emran Askari, Isaac Shiri, et al.
Seminars in Nuclear Medicine (2022) Vol. 52, Iss. 6, pp. 759-780
Open Access | Times Cited: 54
Radiomics in Early Lung Cancer Diagnosis: From Diagnosis to Clinical Decision Support and Education
Yun-Ju Wu, Fu‐Zong Wu, Shu Ching Yang, et al.
Diagnostics (2022) Vol. 12, Iss. 5, pp. 1064-1064
Open Access | Times Cited: 41
Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics
Jihan Wang, Zhengxiang Zhang, Yangyang Wang
Biomolecules (2025) Vol. 15, Iss. 1, pp. 81-81
Open Access | Times Cited: 1
Clinical application of AI-based PET images in oncological patients
Jiaona Dai, Hui Wang, Yuchao Xu, et al.
Seminars in Cancer Biology (2023) Vol. 91, pp. 124-142
Closed Access | Times Cited: 18
PET radiomics for histologic subtype classification of non-small cell lung cancer: a systematic review and meta-analysis
Jucheng Zhang, Xiaohui Zhang, Yan Zhong, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2025)
Closed Access
Impact of harmonization and oversampling methods on radiomics analysis of multi-center imbalanced datasets: application to PET-based prediction of lung cancer subtypes
Dongyang Du, Isaac Shiri, Fereshteh Yousefirizi, et al.
EJNMMI Physics (2025) Vol. 12, Iss. 1
Open Access
PET radiomics in lung cancer: advances and translational challenges
Yongbai Zhang, Wenpeng Huang, Hao Jiao, et al.
EJNMMI Physics (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 3
Radiomics in Oncological PET Imaging: A Systematic Review—Part 1, Supradiaphragmatic Cancers
David Morland, Elizabeth Katherine Anna Triumbari, Luca Boldrini, et al.
Diagnostics (2022) Vol. 12, Iss. 6, pp. 1329-1329
Open Access | Times Cited: 14
Impact of harmonization and oversampling methods on radiomics analysis of multi-center imbalanced datasets: Application to PET-based prediction of lung cancer subtypes
Dongyang Du, Isaac Shiri, Fereshteh Yousefirizi, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 6
Different Clinicopathologic and Computed Tomography Imaging Characteristics of Primary and Acquired EGFR T790M Mutations in Patients with Non-Small-Cell Lung Cancer
Donghui Hou, Weihua Li, Sicong Wang, et al.
Cancer Management and Research (2021) Vol. Volume 13, pp. 6389-6401
Open Access | Times Cited: 14
Current status and prospect of PET-related imaging radiomics in lung cancer
Xin Tang, Fan Wu, Xiaofeng Chen, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 4
Development and validation a radiomics nomogram for diagnosing occult brain metastases in patients with stage IV lung adenocarcinoma
Ping Cong, Qingtao Qiu, Xingchao Li, et al.
Translational Cancer Research (2021) Vol. 10, Iss. 10, pp. 4375-4386
Open Access | Times Cited: 10
Value of contrast-enhanced magnetic resonance imaging-T2WI-based radiomic features in distinguishing lung adenocarcinoma from lung squamous cell carcinoma with solid components >8 mm
Maoyuan Yang, Liang Shi, Tian‐Wei Huang, et al.
Journal of Thoracic Disease (2023) Vol. 15, Iss. 2, pp. 635-648
Open Access | Times Cited: 3
Radiomics in distinguishing between lung adenocarcinoma and lung squamous cell carcinoma: a systematic review and meta-analysis
Lili Shi, Jinli Zhao, Zhichao Wei, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access
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