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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.

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Showing 11 citing articles:

Radiomics-clinical nomogram for preoperative lymph node metastasis prediction in esophageal carcinoma
Xiaotao Geng, Yaping Zhang, Yang Li, et al.
British Journal of Radiology (2024) Vol. 97, Iss. 1155, pp. 652-659
Open Access | Times Cited: 7
Deep Learning for Automatic Gross Tumor Volumes Contouring in Esophageal Cancer Based on Contrast-Enhanced Computed Tomography Images: A Multi-Institutional Study
Shuaitong Zhang, Kunwei Li, Yuchen Sun, et al.
International Journal of Radiation Oncology*Biology*Physics (2024) Vol. 119, Iss. 5, pp. 1590-1600
Closed Access | Times Cited: 4
A Radiomics Model Combining Machine Learning and Neural Networks for High-Accuracy Prediction of Cervical Lymph Node Metastasis on Ultrasound of Head and Neck Squamous Cell Carcinoma
Motoki Fukuda, Sato Eida, Ikuo Katayama, et al.
Oral Surgery Oral Medicine Oral Pathology and Oral Radiology (2025)
Open Access
Radiomics signature for dynamic changes of tumor-infiltrating CD8+ T cells and macrophages in cervical cancer during chemoradiotherapy
Kang Huang, Xuehan Huang, Chengbing Zeng, et al.
Cancer Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Diagnostic accuracy of CT-based radiomics and deep learning for predicting lymph node metastasis in esophageal cancer
Payam Jannatdoust, Parya Valizadeh, Mohammad‐Taha Pahlevan‐Fallahy, et al.
Clinical Imaging (2024) Vol. 113, pp. 110225-110225
Closed Access | Times Cited: 2
Computed tomography radiomics identification of T1–2 and T3–4 stages of esophageal squamous cell carcinoma: two-dimensional or three-dimensional?
Yang Li, Yang Li, Xiaolong Gu, et al.
Abdominal Radiology (2023) Vol. 49, Iss. 1, pp. 288-300
Open Access | Times Cited: 5
CT-based radiomics for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis
Liangsen Liu, H Liao, Yang Zhao, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 1
Value of Computed Tomography Scan for Detecting Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma
Yunqing Zeng, Yaping Liu, Jinhou Li, et al.
Annals of Surgical Oncology (2024)
Closed Access | Times Cited: 1
Radiomics diagnostic performance for predicting lymph node metastasis in esophageal cancer: a systematic review and meta-analysis
Dong Ma, Teli Zhou, Jing Chen, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access
Enhancing lymph node metastasis prediction in adenocarcinoma of the esophagogastric junction: A study combining radiomic with clinical features
Hui‐da Zheng, Yu‐chi Tian, Qiao‐yi Huang, et al.
Medical Physics (2024) Vol. 51, Iss. 12, pp. 9057-9070
Open Access
The application of artificial intelligence in upper gastrointestinal cancers
Xiaoying Huang, Minghao Qin, Mengjie Fang, et al.
Journal of the National Cancer Center (2024) Vol. 5, Iss. 2, pp. 113-131
Open Access
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