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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:

Application Values of 2D and 3D Radiomics Models Based on CT Plain Scan in Differentiating Benign from Malignant Ovarian Tumors
Shiyun Li, Jiaqi Liu, Yuanhuan Xiong, et al.
BioMed Research International (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 21

Showing 21 citing articles:

Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis
He-Li Xu, Tingting Gong, Fang-Hua Liu, et al.
EClinicalMedicine (2022) Vol. 53, pp. 101662-101662
Open Access | Times Cited: 78
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
Performance of CT radiomics in predicting the overall survival of patients with stage III clear cell renal carcinoma after radical nephrectomy
Dong Han, Nan Yu, Yong Yu, et al.
La radiologia medica (2022) Vol. 127, Iss. 8, pp. 837-847
Closed Access | Times Cited: 36
Computed Tomographic Radiomics in Differentiating Histologic Subtypes of Epithelial Ovarian Carcinoma
Mandi Wang, Jose Angelo Udal Perucho, Yangling Hu, et al.
JAMA Network Open (2022) Vol. 5, Iss. 12, pp. e2245141-e2245141
Open Access | Times Cited: 28
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
Analysis of computer-aided diagnostics in the preoperative diagnosis of ovarian cancer: a systematic review
Anna H. Koch, Lara S. Jeelof, Caroline L. P. Muntinga, et al.
Insights into Imaging (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 11
Different radiomics annotation methods comparison in rectal cancer characterisation and prognosis prediction: a two-centre study
Ying Zhu, Yaru Wei, Zhongwei Chen, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 2
Radiomics on slice-reduced versus full-chest computed tomography for diagnosis and staging of interstitial lung disease in systemic sclerosis: A comparative analysis
Anja A Joye, Marta Bogowicz, Janine Gote-Schniering, et al.
European Journal of Radiology Open (2024) Vol. 13, pp. 100596-100596
Open Access | Times Cited: 2
Enhanced and unenhanced: Radiomics models for discriminating between benign and malignant cystic renal masses on CT images: A multi-center study
Lesheng Huang, Wenhui Feng, Wenxiang Lin, et al.
PLoS ONE (2023) Vol. 18, Iss. 9, pp. e0292110-e0292110
Open Access | Times Cited: 5
Cystic renal mass screening: machine-learning-based radiomics on unenhanced computed tomography
Lesheng Huang, Yongsong Ye, Jun Chen, et al.
Diagnostic and Interventional Radiology (2023)
Open Access | Times Cited: 4
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
Non-Invasive Prediction of Survival Time of Midline Glioma Patients Using Machine Learning on Multiparametric MRI Radiomics Features
Dabiao Deng, Yuting Liao, Jiangfen Zhou, et al.
Frontiers in Neurology (2022) Vol. 13
Open Access | Times Cited: 7
Lack of incremental value of three-dimensional measurement in assessing invasiveness for lung cancer
Meng-Min Wang, Jiaqi Li, Shihua Dou, et al.
European Journal of Cardio-Thoracic Surgery (2023) Vol. 64, Iss. 6
Open Access | Times Cited: 3
Diagnostic value of a CT-based radiomics nomogram for discrimination of benign and early stage malignant ovarian tumors
Jia Chen, Fei Yang, Chanzhen Liu, et al.
European journal of medical research (2023) Vol. 28, Iss. 1
Open Access | Times Cited: 3
Combined hepatocellular-cholangiocarcinoma and hepatocellular carcinoma: Differentiation using radiomics based on Multitemporal CT images
Rong Xu, Guo Le, Guanjun Chen, et al.
Research Square (Research Square) (2024)
Open Access
Classification of Ovarian Cancer with Multimodal Data Using AI Technology– A Review
P Suma, K Suma, B P Lakshmishree, et al.
(2024), pp. 131-136
Closed Access
Application of artificial intelligence in CT and MR imaging of ovarian cancer
Lili Zhou, Chinting Wong, Yubo Li, et al.
Chinese Journal of Academic Radiology (2023) Vol. 6, Iss. 4, pp. 170-178
Closed Access | Times Cited: 1
Advances in Imaging Histology in Ovarian Cancer
浩 杨
Advances in Clinical Medicine (2023) Vol. 13, Iss. 08, pp. 12230-12235
Closed Access
Artificial Intelligence Performance in Image-Based Ovarian Cancer Identification: A Systematic Review and Meta-Analysis
He-Li Xu, Fang-Hua Liu, Hongyu Chen, et al.
SSRN Electronic Journal (2022)
Closed Access
CT-based machine learning radiomics predict CCR5 expression level and survival in ovarian cancer
Sheng Wan, Tianfan Zhou, Ronghua Che, et al.
Research Square (Research Square) (2022)
Open Access
CT-Based Radiomics and Machine Learning for Differentiating Benign, Borderline, and Early-stage Malignant Ovarian Tumors: A Multi-Class Classification and Multi-Model Comparation Study
Jia Chen, Lei Liu, Ziying He, et al.
Research Square (Research Square) (2022)
Open Access
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