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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 18 citing articles:

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
AI tool for predicting MGMT methylation in glioblastoma for clinical decision support in resource limited settings
Felipe Cicci Farinha Restini, Tarraf Torfeh, Souha Aouadi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Diagnostic Accuracy of MRI in Detecting Stromal Invasion in Early Cervical Cancer Patients Taking Histopathology as Gold Standard
Nosheen Ahmad, Marryum Mukhtar, Aamna Gilani, et al.
Pakistan Journal of Health Sciences (2025), pp. 53-57
Closed Access
Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics Model for Preoperative Predicting the Deep Stromal Invasion in Patients with Early Cervical Cancer
Haowen Yan, Gaoting Huang, Zhihe Yang, et al.
Deleted Journal (2024) Vol. 37, Iss. 1, pp. 230-246
Open Access | Times Cited: 3
Diagnostic Performance of Selected MRI-Derived Radiomics Able to Discriminate Progression-Free and Overall Survival in Patients with Midline Glioma and the H3F3AK27M Mutation
Maria-Fatima Chilaca-Rosas, Melissa Garcia-Lezama, Sergio Moreno‐Jiménez, et al.
Diagnostics (2023) Vol. 13, Iss. 5, pp. 849-849
Open Access | Times Cited: 8
Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy
Rongrong Wu, Yimin Zhou, Xingyun Xie, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 8
Preoperative Tumor Texture Analysis on MRI for High-Risk Disease Prediction in Endometrial Cancer: A Hypothesis-Generating Study
Maura Miccò, Benedetta Gui, Luca Russo, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 11, pp. 1854-1854
Open Access | Times Cited: 11
Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early‐Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study
Mei Xiao, Ting Qian, Le Fu, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 59, Iss. 4, pp. 1394-1406
Closed 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
Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma
Xuefang Zhang, Hong-yuan Wu, Xu-Wei Liang, et al.
BMC Women s Health (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Self-supervised learning for multi-center magnetic resonance imaging harmonization without traveling phantoms
Xiao Chang, Xin Cai, Yibo Dan, et al.
Physics in Medicine and Biology (2022) Vol. 67, Iss. 14, pp. 145004-145004
Closed Access | Times Cited: 6
Automated Prediction of Neoadjuvant Chemoradiotherapy Response in Locally Advanced Cervical Cancer Using Hybrid Model-Based MRI Radiomics
Hua Yang, Yinan Xu, Mohan Dong, et al.
Diagnostics (2023) Vol. 14, Iss. 1, pp. 5-5
Open Access | Times Cited: 3
Editorial for “Deep Learning Nomogram for the Identification of Deep Stromal Invasion in Patients With Early‐Stage Cervical Adenocarcinoma and Adenosquamous Carcinoma: A Multicenter Study”
Nikolaos‐Achilleas Arkoudis, Nikolaos Kelekis
Journal of Magnetic Resonance Imaging (2023) Vol. 59, Iss. 4, pp. 1407-1408
Closed Access | Times Cited: 1
Development of a machine learning model for predicting the expression of proteins associated with targeted therapy in endometrial cancer
Chenwen Sun, Qianling Li, Yanan Huang, et al.
Research Square (Research Square) (2024)
Open Access
Preoperative magnetic resonance imaging-radiomics in cervical cancer: a systematic review and meta-analysis
Linyong Wu, Songhua Li, Shaofeng Li, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access
Multi-parametric MRI-based Peritumoral Radiomics for Stage IIA and IIB Classification of Cervical Cancer：A Multicenter Study
Ying Wang, Weixiao Liu, Yulian Chen, et al.
Research Square (Research Square) (2024)
Open Access
Automated Prediction of Radiotherapy Sensitivity Using Hybrid Model-Based MRI Radiomics in Locally Advanced Cervical Cancer
Hua Yang, Yinan Xu, Mohan Dong, et al.
Research Square (Research Square) (2023)
Open Access
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