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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 27 citing articles:

Application of magnetic resonance imaging radiomics in endometrial cancer: a systematic review and meta-analysis
Meng-Lin Huang, Jing Ren, Zhengyu Jin, et al.
La radiologia medica (2024) Vol. 129, Iss. 3, pp. 439-456
Closed Access | Times Cited: 6
Multiparametric MRI radiomics improves preoperative diagnostic performance for local staging in patients with endometrial cancer
Ruqi Fang, Na Lin, Shuping Weng, et al.
Abdominal Radiology (2024) Vol. 49, Iss. 3, pp. 875-887
Closed Access | Times Cited: 4
Development and validation of clinical-radiomics deep learning model based on MRI for endometrial cancer molecular subtypes classification
Wenyi Yue, R. Han, Haijie Wang, et al.
Insights into Imaging (2025) Vol. 16, Iss. 1
Open Access
Accuracy of radiomics in the diagnosis and preoperative high-risk assessment of endometrial cancer: a systematic review and meta-analysis
Junmei He, Yurong Liu, Jinzhu Li, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 3
Radiomics model based on multi-sequence MRI for preoperative prediction of ki-67 expression levels in early endometrial cancer
Si-Xuan Ding, Yu-Feng Sun, Huan Meng, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 7
Preoperative Imaging Evaluation of Endometrial Cancer in FIGO 2023
Aki Kido, Yuki Himoto, Yasuhisa Kurata, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 60, Iss. 4, pp. 1225-1242
Closed Access | Times Cited: 5
Artificial Intelligence and Radiomics for Endometrial Cancer MRI: Exploring the Whats, Whys and Hows
Elisabetta Leo, Arnaldo Stanzione, Mariaelena Miele, et al.
Journal of Clinical Medicine (2023) Vol. 13, Iss. 1, pp. 226-226
Open Access | Times Cited: 5
Classification of retinoblastoma-1 gene mutation with machine learning-based models in bladder cancer
Okan İnce, Hülya Yıldız, Tanju Kisbet, et al.
Heliyon (2022) Vol. 8, Iss. 4, pp. e09311-e09311
Open Access | Times Cited: 8
An Applicable Machine Learning Model Based on Preoperative Examinations Predicts Histology, Stage, and Grade for Endometrial Cancer
Ying Feng, Zhixiang Wang, Meizhu Xiao, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 8
Nodal infiltration in endometrial cancer: a prediction model using best subset regression
Yuka Matsumoto, Yuki Himoto, Mizuho Nishio, et al.
European Radiology (2023) Vol. 34, Iss. 5, pp. 3375-3384
Closed Access | Times Cited: 4
The Applicability of Artificial Intelligence in Predicting the Depth of Myometrial Invasion on MRI Studies—A Systematic Review
Octavia Petrila, Anca-Elena Stefan, Dumitru Gafițanu, et al.
Diagnostics (2023) Vol. 13, Iss. 15, pp. 2592-2592
Open Access | Times Cited: 4
An MR-based radiomics nomogram including information from the peritumoral region to predict deep myometrial invasion in stage I endometrioid adenocarcinoma: a preliminary study
Bin Yan, Tingting Zhao, Zhihao Li, et al.
British Journal of Radiology (2023) Vol. 96, Iss. 1151
Open Access | Times Cited: 4
Multiparameter MRI-based radiomics analysis for preoperative prediction of type II endometrial cancer
Yingying Cao, Wei Zhang, Xiaorong Wang, et al.
Heliyon (2024) Vol. 10, Iss. 12, pp. e32940-e32940
Open Access | Times Cited: 1
Role of Machine Learning (ML)-Based Classification Using Conventional 18F-FDG PET Parameters in Predicting Postsurgical Features of Endometrial Cancer Aggressiveness
Carolina Bezzi, Alice Bergamini, Gregory Mathoux, et al.
Cancers (2023) Vol. 15, Iss. 1, pp. 325-325
Open Access | Times Cited: 3
Detection of EGFR mutations in early-stage lung adenocarcinoma by machine learning-based radiomics
Kenshiro Omura, Yu Murakami, Kohei Hashimoto, et al.
Translational Cancer Research (2023) Vol. 12, Iss. 4, pp. 837-847
Open Access | Times Cited: 3
Advances in Radiomics Research for Endometrial Cancer: A Comprehensive Review
Wenxiu Guo, Tong Wang, Binglin Lv, et al.
Journal of Cancer (2023) Vol. 14, Iss. 18, pp. 3523-3531
Open Access | Times Cited: 3
The Added Value of ADC-based Nomogram in Assessing the Depth of Myometrial Invasion of Endometrial Endometrioid Adenocarcinoma
Xiaoliang Ma, Songqi Cai, Jingjing Lu, et al.
Academic Radiology (2023) Vol. 31, Iss. 6, pp. 2324-2333
Closed Access | Times Cited: 3
Multi-parametric MRI-based radiomics for preoperative prediction of multiple biological characteristics in endometrial cancer
Changjun Ma, Ying Zhao, Qingling Song, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 3
The value of machine learning in preoperative identification of lymph node metastasis status in endometrial cancer: a systematic review and meta-analysis
Zhonglian Ren, Banghong Chen, Changying Hong, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 3
Preoperative assessment of high-grade endometrial cancer using a radiomic signature and clinical indicators
Tao Zheng, Jiangyang Pan, Dan Du, et al.
Future Oncology (2023) Vol. 19, Iss. 8, pp. 587-601
Closed Access | Times Cited: 1
Development and external validation of a nomogram for predicting overall survival of patients with non-endometrioid endometrial cancer: A population-based analysis
Jingya Chen, Xiaorong Wang, Qinfeng Xu, et al.
Heliyon (2024) Vol. 10, Iss. 7, pp. e28864-e28864
Open Access
Reply to Letter to the Editor: Nodal infiltration in endometrial cancer: a prediction model using best subset regression
Yuki Himoto, Mizuho Nishio, Koji Yamanoi, et al.
European Radiology (2024) Vol. 34, Iss. 12, pp. 7696-7697
Closed Access
A deep learning framework for predicting endometrial cancer from cytopathologic images with different staining styles
R. Wang, Qing Li, Guizhi Shi, et al.
PLoS ONE (2024) Vol. 19, Iss. 7, pp. e0306549-e0306549
Open Access
Multiparametric MRI radiomics for predicting disease-free survival and high-risk histopathological features for tumor recurrence in endometrial cancer
Mary Renton, Mina Fakhriyehasl, Jessica Weiss, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access
Multi-modality MRI radiomics phenotypes in intermediate-high risk endometrial cancer: correlations with histopathology and prognosis
Jiacheng Song, Xiaoting Jiang, Yao Lu, et al.
Japanese Journal of Radiology (2024)
Closed Access
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