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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:

CT-based machine learning radiomics predicts CCR5 expression level and survival in ovarian cancer
Sheng Wan, Tianfan Zhou, Ronghua Che, et al.
Journal of Ovarian Research (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 23

Showing 23 citing articles:

A systematic review and meta-analysis of CT and MRI radiomics in ovarian cancer: methodological issues and clinical utility
Meng-Lin Huang, Jing Ren, Zhengyu Jin, et al.
Insights into Imaging (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 16
Predicting progression-free survival in patients with epithelial ovarian cancer using an interpretable random forest model
Lian Jian, Xiaoyan Chen, Pingsheng Hu, et al.
Heliyon (2024) Vol. 10, Iss. 15, pp. e35344-e35344
Open Access | Times Cited: 4
Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors
Shuangyang Mo, Cheng Huang, Yingwei Wang, et al.
BMC Medical Imaging (2025) Vol. 25, Iss. 1
Open Access
CT-based Machine Learning Radiomics Modeling: Survival Prediction and Mechanism Exploration in Ovarian Cancer Patients
Rixin Su, Yu Zhang, LI Xue-ya, et al.
Academic Radiology (2025)
Closed Access
An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer
Yi Nan, Shuangyang Mo, Yan Zhang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Comparing the Effectiveness of Artificial Intelligence Models in Predicting Ovarian Cancer Survival: A Systematic Review
Farkhondeh Asadi, Milad Rahimi, Nahid Ramezanghorbani, et al.
Cancer Reports (2025) Vol. 8, Iss. 3
Open Access
Computed Tomography-Based Radiomics to Predict FOXM1 Expression and Overall Survival in Patients with Clear Cell Renal Cell Carcinoma
Jingwei Zhao, Qi Zhang, Yan Chen, et al.
Academic Radiology (2024) Vol. 31, Iss. 9, pp. 3635-3646
Closed Access | Times Cited: 3
Long Short-Term Memory-Deep Belief Network-Based Gene Expression Data Analysis for Prostate Cancer Detection and Classification
Bijaya Kumar Sethi, Debabrata Singh, Saroja Kumar Rout, et al.
IEEE Access (2023) Vol. 12, pp. 1508-1524
Open Access | Times Cited: 8
CT radiomics prediction of CXCL9 expression and survival in ovarian cancer
Rui Gu, Siyi Tan, Yuping Xu, et al.
Journal of Ovarian Research (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 5
Chemokine systems in oncology: From microenvironment modulation to nanocarrier innovations
Meng Guan, Shuhan Liu, Yong‐Guang Yang, et al.
International Journal of Biological Macromolecules (2024) Vol. 268, pp. 131679-131679
Closed Access | Times Cited: 1
Research Progress of Imaging Histology in the Prognosis of Ovarian Cancer Immunotherapy
子金 郑
Advances in Clinical Medicine (2024) Vol. 14, Iss. 05, pp. 759-766
Closed Access | Times Cited: 1
Predicting CD27 expression and clinical prognosis in serous ovarian cancer using CT-based radiomics
Chen Zhang, Heng Cui, Yi Li, et al.
Journal of Ovarian Research (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 1
New Trends in Ovarian Cancer Diagnosis Using Deep Learning: A Systematic Review
Mohamed El-Khatib, Dan Popescu, Oana Mihaela Teodor, et al.
IEEE Access (2024) Vol. 12, pp. 116587-116608
Open Access | Times Cited: 1
A Tabular Variational Auto Encoder-Based Hybrid Model for Imbalanced Data Classification With Feature Selection
Asha Abraham, Habeeb Shaik Mohideen, R. Kayalvizhi
IEEE Access (2023) Vol. 11, pp. 122760-122771
Open Access | Times Cited: 2
Ct-Based Radiomics Predicts Cd38 Expression: Indirectly Reflects Clinical Prognosis in Epithelial Ovarian Cancer
Yuan Yao, Haijin Zhang, Hui Liu, et al.
(2024)
Open Access
CT-based radiomics predicts CD38 expression and indirectly reflects clinical prognosis in epithelial ovarian cancer
Yuan Yao, Haijin Zhang, Hui Liu, et al.
Heliyon (2024) Vol. 10, Iss. 12, pp. e32910-e32910
Open Access
Contrast-Enhanced Computed Tomography-Based Machine Learning Radiomics Predicts IDH1 Expression and Clinical Prognosis in Head and Neck Squamous Cell Carcinoma
Le Wang, Jilin Peng, Baohong Wen, et al.
Academic Radiology (2024)
Open Access
An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer
Yi Nan, Shuangyang Mo, Yan Zhang, et al.
Research Square (Research Square) (2024)
Open Access
Contrast-Enhanced Computed Tomography Radiomics Predicts Colony-Stimulating Factor 3 Expression and Clinical Prognosis in Ovarian Cancer
Xiaofeng Lv, Xiaoxue Zhang, Ruyue Gong, et al.
Academic Radiology (2024)
Open Access
Homologous recombination deficiency (HRD) diagnostics: underlying mechanisms and new perspectives
Andrey Kechin, Maksim Koryukov, Regina Mikheeva, et al.
Cancer and Metastasis Reviews (2024) Vol. 44, Iss. 1
Closed Access
Construction of 3D and 2D contrast-enhanced CT radiomics for prediction of CGB3 expression level and clinical prognosis in bladder cancer
Yuanfeng Zhang, Zhuangyong Xu, Shaoxu Wu, et al.
Heliyon (2023) Vol. 9, Iss. 9, pp. e20335-e20335
Open Access | Times Cited: 1
Research Progress on Application of Artificial Intelligence in Gynecological Malignant Tumor
紫均 陈
Advances in Clinical Medicine (2023) Vol. 13, Iss. 06, pp. 10542-10548
Closed Access
CT-based radiomics predicts CD38 expression: indirectly reflects clinical prognosis in epithelial ovarian cancer
Yuan Yao, Haijin Zhang, Hui Liu, et al.
Research Square (Research Square) (2023)
Open Access
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