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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 Analysis of Multiparametric MRI for the Preoperative Prediction of Lymph Node Metastasis in Cervical Cancer
Lina Hou, Wei Zhou, Jialiang Ren, et al.
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

MRI-based multiregional radiomics for predicting lymph nodes status and prognosis in patients with resectable rectal cancer
Hang Li, Xiaoli Chen, Huan Liu, et al.
Frontiers in Oncology (2023) Vol. 12
Open Access | Times Cited: 22
The role of lymph nodes in cervical cancer: incidence and identification of lymph node metastases—a literature review
Ester P. Olthof, Maaike A. van der Aa, Judit A. Adam, et al.
International Journal of Clinical Oncology (2021) Vol. 26, Iss. 9, pp. 1600-1610
Closed Access | Times Cited: 47
Intra- and peri-tumoral MRI radiomics features for preoperative lymph node metastasis prediction in early-stage cervical cancer
Zhenhua Zhang, Xiaojie Wan, Xiyao Lei, et al.
Insights into Imaging (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 20
Prediction of lymph node metastasis in operable cervical cancer using clinical parameters and deep learning with MRI data: a multicentre study
Fengying Qin, Xinyan Sun, Mingke Tian, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
A meta-analysis of MRI-based radiomic features for predicting lymph node metastasis in patients with cervical cancer
Longchao Li, Jing Zhang, Xia Zhe, et al.
European Journal of Radiology (2022) Vol. 151, pp. 110243-110243
Open Access | Times Cited: 27
Radiomics Based on T2-Weighted Imaging and Apparent Diffusion Coefficient Images for Preoperative Evaluation of Lymph Node Metastasis in Rectal Cancer Patients
Chunli Li, Jiandong Yin
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 31
Radiomic Score as a Potential Imaging Biomarker for Predicting Survival in Patients With Cervical Cancer
Handong Li, Miaochen Zhu, Lian Jian, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 27
Cer-ConvN3Unet: an end-to-end multi-parametric MRI-based pipeline for automated detection and segmentation of cervical cancer
Shudong Xia, Bo Zhao, Yingming Li, et al.
European Radiology Experimental (2025) Vol. 9, Iss. 1
Open Access
Imaging based artificial intelligence for predicting lymph node metastasis in cervical cancer patients: a systematic review and meta-analysis
C. Jiang, Xiujuan Li, Zhiyi Zhou, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access
Computed tomography–based radiomics modeling to predict patient overall survival in cervical cancer with intensity-modulated radiotherapy combined with concurrent chemotherapy
Lihong Xiao, Youhua Wang, Xiangxiang Shi, et al.
Journal of International Medical Research (2025) Vol. 53, Iss. 3
Open Access
A Hybrid Model-Based Clinicopathological Features and Radiomics Based on Conventional MRI for Predicting Lymph Node Metastasis and DFS in Cervical Cancer
Mingke Tian, Fengying Qin, Xinyan Sun, et al.
Deleted Journal (2025)
Closed Access
Optimisation and evaluation of the random forest model in the efficacy prediction of chemoradiotherapy for advanced cervical cancer based on radiomics signature from high-resolution T2 weighted images
Defeng Liu, Xiaohang Zhang, Tao Zheng, et al.
Archives of Gynecology and Obstetrics (2021) Vol. 303, Iss. 3, pp. 811-820
Open Access | Times Cited: 24
Comparison of preoperative CT- and MRI-based multiparametric radiomics in the prediction of lymph node metastasis in rectal cancer
Yue Niu, Xiaoping Yu, Lu Wen, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 9
Radiomics analysis based on multiparametric magnetic resonance imaging for differentiating early stage of cervical cancer
Feng Wu, Rui Zhang, Feng Li, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 3
Feasibility of MRI-based radiomics features for predicting lymph node metastases and VEGF expression in cervical cancer
Xijia Deng, Meiling Liu, Jianqing Sun, et al.
European Journal of Radiology (2020) Vol. 134, pp. 109429-109429
Open Access | Times Cited: 26
Clinical value of MRI, serum SCCA, and CA125 levels in the diagnosis of lymph node metastasis and para-uterine infiltration in cervical cancer
Chao Ran, Jian Sun, Yunhui Qu, et al.
World Journal of Surgical Oncology (2021) Vol. 19, Iss. 1
Open Access | Times Cited: 23
Feasibility of Predicting Pelvic Lymph Node Metastasis Based on IVIM-DWI and Texture Parameters of the Primary Lesion and Lymph Nodes in Patients with Cervical Cancer
Yu Zhang, Kai-yue Zhang, Haodong Jia, et al.
Academic Radiology (2021) Vol. 29, Iss. 7, pp. 1048-1057
Closed Access | Times Cited: 18
Predicting Disease-Free Survival With Multiparametric MRI-Derived Radiomic Signature in Cervical Cancer Patients Underwent CCRT
Bing Liu, Zhen Sun, Ziliang Xu, et al.
Frontiers in Oncology (2022) Vol. 11
Open Access | Times Cited: 13
Diagnostic performance of ADC values and MRI-based radiomics analysis for detecting lymph node metastasis in patients with cervical cancer: A systematic review and meta-analysis
Jing Ren, Yuan Li, Xinyu Liu, et al.
European Journal of Radiology (2022) Vol. 156, pp. 110504-110504
Closed Access | Times Cited: 13
Preoperative MR radiomics based on high-resolution T2-weighted images and amide proton transfer-weighted imaging for predicting lymph node metastasis in rectal adenocarcinoma
Qiurong Wei, Wenjing Yuan, Ziqi Jia, et al.
Abdominal Radiology (2022) Vol. 48, Iss. 2, pp. 458-470
Closed Access | Times Cited: 13
Preoperative Assessment of MRI‐Invisible Early‐Stage Endometrial Cancer With MRI‐Based Radiomics Analysis
Xiaoting Jiang, Jiacheng Song, Aining Zhang, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 58, Iss. 1, pp. 247-255
Closed Access | Times Cited: 12
The application of radiomics machine learning models based on multimodal MRI with different sequence combinations in predicting cervical lymph node metastasis in oral tongue squamous cell carcinoma patients
Sheng Liu, Aihua Zhang, Jianjun Xiong, et al.
Head & Neck (2023) Vol. 46, Iss. 3, pp. 513-527
Closed Access | Times Cited: 6
A Novel Ultrasound-Based Radiomics Model for the Preoperative Prediction of Lymph Node Metastasis in Cervical Cancer
Xianyue Yang, Yan Wang, Jingshu Zhang, et al.
Ultrasound in Medicine & Biology (2024) Vol. 50, Iss. 12, pp. 1793-1799
Closed Access | Times Cited: 2
MRI radiomics combined with clinicopathologic features to predict disease-free survival in patients with early-stage cervical cancer
Xiaoting Jiang, Jiacheng Song, Shaofeng Duan, et al.
British Journal of Radiology (2022) Vol. 95, Iss. 1136
Open Access | Times Cited: 10
Nomogram Predicting Lymph Node Metastasis in the Early-Stage Cervical Cancer
Shimin Yang, Chunli Liu, Chunbo Li, et al.
Frontiers in Medicine (2022) Vol. 9
Open Access | Times Cited: 8
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