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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 1-25 of 26 citing articles:

Current Paradigm and Future Directions in the Management of Nodal Disease in Locally Advanced Cervical Cancer
Elki Sze-Nga Cheung, Philip Yuguang Wu
Cancers (2025) Vol. 17, Iss. 2, pp. 202-202
Open Access | Times Cited: 2
Radiomics systematic review in cervical cancer: gynecological oncologists’ perspective
Nicolò Bizzarri, Luca Russo, Miriam Dolciami, et al.
International Journal of Gynecological Cancer (2023) Vol. 33, Iss. 10, pp. 1522-1541
Closed Access | Times Cited: 15
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
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
Pre-Treatment and Pre-Brachytherapy MRI first-order Radiomic Features by a Commercial software as survival predictors in radiotherapy for cervical cancer Objectives
Wiwatchai Sittiwong, Pittaya Dankulchai, Pitchayut Wongsuwan, et al.
Clinical and Translational Radiation Oncology (2025) Vol. 53, pp. 100965-100965
Open Access
Harnessing unsupervised machine learning with [18F]FDG PET/CT to develop a composite model for predicting overall survival in cervical cancer patients undergoing concurrent chemoradiotherapy
Jinyu Shi, Lian Wang, Min Zhou, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access
Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer
Mari K. Halle, Erlend Hodneland, Kari S. Wagner‐Larsen, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
An Integrated Clinical‐MR Radiomics Model to Estimate Survival Time in Patients With Endometrial Cancer
Xingfeng Li, Diana Marcus, James Russell, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 57, Iss. 6, pp. 1922-1933
Open Access | Times Cited: 9
Development and validation of a radiomics-based nomogram for the prediction of postoperative malnutrition in stage IB1-IIA2 cervical carcinoma
Wenke Yu, Hong’en Xu, Fangjie Chen, et al.
Frontiers in Nutrition (2023) Vol. 10
Open Access | Times Cited: 5
Staging of Cervical Cancer: A Practical Approach Using MRI and FDG PET
Yulia Lakhman, Emily A. Aherne, Vetri Sudar Jayaprakasam, et al.
American Journal of Roentgenology (2023) Vol. 221, Iss. 5, pp. 633-648
Closed Access | Times Cited: 4
MRI‐based radiomic signatures for pretreatment prognostication in cervical cancer
Kari S. Wagner‐Larsen, Erlend Hodneland, Kristine E. Fasmer, et al.
Cancer Medicine (2023) Vol. 12, Iss. 20, pp. 20251-20265
Open Access | Times Cited: 4
The Utility of Contrast-Enhanced Magnetic Resonance Imaging in Uterine Cervical Cancer: A Systematic Review
Giacomo Avesani, Alessio Perazzolo, Andrea Amerighi, et al.
Life (2023) Vol. 13, Iss. 6, pp. 1368-1368
Open Access | Times Cited: 4
Pre-treatment T2-weighted magnetic resonance radiomics for prediction of loco-regional recurrence after image-guided adaptive brachytherapy for locally advanced cervical cancer
Pittaya Dankulchai, Natthakorn Thanamitsomboon, Wiwatchai Sittiwong, et al.
Journal of Contemporary Brachytherapy (2024) Vol. 16, Iss. 3, pp. 193-201
Open Access | Times Cited: 1
Artificial Intelligence in Obstetric and Gynecological MR Imaging
Tsukasa Saida, Wenchao Gu, Sodai Hoshiai, et al.
Magnetic Resonance in Medical Sciences (2024)
Open Access | Times Cited: 1
Prediction model based on radiomics and clinical features for preoperative lymphovascular invasion in gastric cancer patients
Ping Wang, Kaige Chen, Ying Han, et al.
Future Oncology (2023) Vol. 19, Iss. 23, pp. 1613-1626
Open Access | Times Cited: 3
Preoperative prediction of cervical cancer survival using a high-resolution MRI-based radiomics nomogram
Jia Li, Hao Zhou, Xiaofei Lü, et al.
BMC Medical Imaging (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 2
Pre-Treatment and Pre-Brachytherapy MRI First-Order Radiomic Features by a Commercial Software as Survival Predictors in Radiotherapy for Cervical Cancer
Wiwatchai Sittiwong, Pittaya Dankulchai, Pitchayut Wongsuwan, et al.
(2024)
Closed Access
MRI Radiomics and Nutritional-Inflammatory Biomarkers: A Powerful Combination for Predicting Progression-Free Survival in Cervical Cancer Patients Undergoing Concurrent Chemoradiotherapy
Qi Yan, Menghan Wu, Jing Zhang, et al.
Research Square (Research Square) (2024)
Open Access
MRI radiomics and nutritional-inflammatory biomarkers: a powerful combination for predicting progression-free survival in cervical cancer patients undergoing concurrent chemoradiotherapy
Qi Yan, Menghan Wu, Jing Zhang, et al.
Cancer Imaging (2024) Vol. 24, Iss. 1
Open Access
Nomograms combining clinical factors and apparent diffusion coefficient to predict downstaging and progression-free survival after concurrent chemoradiotherapy in patients with cervical cancer
Jiawei Fan, Wenfei Li, Mengyu Cheng, et al.
Acta Radiologica (2024) Vol. 65, Iss. 11, pp. 1430-1439
Closed Access
Progression-Free Survival Prediction for Locally Advanced Cervical Cancer after Chemoradiotherapy with MRI-based Radiomics
Shanshan Tang, Allen Yen, Kai Wang, et al.
Clinical Oncology (2024) Vol. 38, pp. 103702-103702
Closed Access
Preoperative prediction of cervical cancer survival using a high-resolution MRI-based radiomics nomogram
Jia Li, Hao Zhou, Xiaofei Lü, et al.
Research Square (Research Square) (2023)
Open Access
Patient survival prediction in locally advanced cervical squamous cell carcinoma using MRI-based radiomics: retrospective cohort study
Anan Bseiso, Muhammad Saqib, Muhammad Sherdil Saigol, et al.
Annals of Medicine and Surgery (2023) Vol. 85, Iss. 11, pp. 5328-5336
Open Access
A systematic review of radiomics for predicting treatment response and survival in locally advanced cervical cancer: positive results or optimistic illusions?
Lizhao Huang, Lu Li, Xiaoqi Huang, et al.
Clinical and Translational Imaging (2023) Vol. 12, Iss. 3, pp. 263-285
Closed Access
Radiomics in Gynaecological Imaging: A State-of-the-Art Review
Paolo Niccolò Franco, Federica Vernuccio, Cesare Maino, et al.
Applied Sciences (2023) Vol. 13, Iss. 21, pp. 11839-11839
Open Access
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