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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:

A predictive nomogram for individualized recurrence stratification of bladder cancer using multiparametric MRI and clinical risk factors
Xiaopan Xu, Huanjun Wang, Peng Du, et al.
Journal of Magnetic Resonance Imaging (2019) Vol. 50, Iss. 6, pp. 1893-1904
Open Access | Times Cited: 68

Showing 1-25 of 68 citing articles:

Systemic immune-inflammation index predicts prognosis of bladder cancer patients after radical cystectomy
Wentao Zhang, Ruiliang Wang, Wenchao Ma, et al.
Annals of Translational Medicine (2019) Vol. 7, Iss. 18, pp. 431-431
Open Access | Times Cited: 86
Artificial intelligence: A promising frontier in bladder cancer diagnosis and outcome prediction
Soheila Borhani, Reza Borhani, André Kajdacsy-Balla
Critical Reviews in Oncology/Hematology (2022) Vol. 171, pp. 103601-103601
Open Access | Times Cited: 52
Quantitative Identification of Major Depression Based on Resting-State Dynamic Functional Connectivity: A Machine Learning Approach
Baoyu Yan, Xiaopan Xu, Mengwan Liu, et al.
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 61
Elaboration of a multisequence MRI-based radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer: a double-center study
Huanjun Wang, Xiaopan Xu, Xi Zhang, et al.
European Radiology (2020) Vol. 30, Iss. 9, pp. 4816-4827
Closed Access | Times Cited: 59
Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review
Kangwen He, Xiaoyan Meng, Yanchun Wang, et al.
Diagnostics (2024) Vol. 14, Iss. 4, pp. 442-442
Open Access | Times Cited: 6
Predicting non-muscle invasive bladder cancer outcomes using artificial intelligence: a systematic review using APPRAISE-AI
Jethro C.C. Kwong, Jeremy Wu, Shamir Malik, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 6
Elaboration of a multimodal MRI-based radiomics signature for the preoperative prediction of the histological subtype in patients with non-small-cell lung cancer
Xing Tang, Xiaopan Xu, Zhiping Han, et al.
BioMedical Engineering OnLine (2020) Vol. 19, Iss. 1
Open Access | Times Cited: 43
Radiomics based on multisequence magnetic resonance imaging for the preoperative prediction of peritoneal metastasis in ovarian cancer
Xiaoli Song, Jialiang Ren, Ting-Yu Yao, et al.
European Radiology (2021) Vol. 31, Iss. 11, pp. 8438-8446
Closed Access | Times Cited: 33
Intratumoral and peritumoral CT-based radiomics strategy reveals distinct subtypes of non-small-cell lung cancer
Xing Tang, Haolin Huang, Peng Du, et al.
Journal of Cancer Research and Clinical Oncology (2022) Vol. 148, Iss. 9, pp. 2247-2260
Closed Access | Times Cited: 25
A nomogram strategy for identifying the subclassification of IDH mutation and ATRX expression loss in lower-grade gliomas
Shiman Wu, Xi Zhang, Wenting Rui, et al.
European Radiology (2022) Vol. 32, Iss. 5, pp. 3187-3198
Closed Access | Times Cited: 24
Enhancing recurrence risk prediction for bladder cancer using multi-sequence MRI radiomics
Guoqiang Yang, Jingjing Bai, Min Hao, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 5
Study Progress of Radiomics With Machine Learning for Precision Medicine in Bladder Cancer Management
Lingling Ge, Yuntian Chen, Chunyi Yan, et al.
Frontiers in Oncology (2019) Vol. 9
Open Access | Times Cited: 40
Combining Multiparametric MRI Radiomics Signature With the Vesical Imaging-Reporting and Data System (VI-RADS) Score to Preoperatively Differentiate Muscle Invasion of Bladder Cancer
Zongtai Zheng, Feijia Xu, Zhuoran Gu, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 27
Application of contrast-enhanced CT radiomics in prediction of early recurrence of locally advanced oesophageal squamous cell carcinoma after trimodal therapy
Sun Tang, Jing Ou, Jun Liu, et al.
Cancer Imaging (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 27
Preoperative prediction of KRAS mutation status in colorectal cancer using a CT-based radiomics nomogram
Ting Xue, Hui Peng, Qiaoling Chen, et al.
British Journal of Radiology (2022) Vol. 95, Iss. 1134
Open Access | Times Cited: 19
Deep learning signature based on multiphase enhanced CT for bladder cancer recurrence prediction: a multi-center study
Hexiang Wang, Meng Zhang, Jianguo Miao, et al.
EClinicalMedicine (2023) Vol. 66, pp. 102352-102352
Open Access | Times Cited: 12
AI predicting recurrence in non-muscle-invasive bladder cancer: systematic review with study strengths and weaknesses
Saram Abbas, Rishad Shafik, Naeem Soomro, et al.
Frontiers in Oncology (2025) Vol. 14
Open Access
Global research trends and hotspots on imaging of bladder cancer: A bibliometric and visual analysis from 1981 to 2023
Zijian Gong, Z. G. Liu, Jianghua Zhu, et al.
Medicine (2025) Vol. 104, Iss. 12, pp. e41907-e41907
Open Access
Recent Advances in Artificial Intelligence for Precision Diagnosis and Treatment of Bladder Cancer: A Review
Xiangxiang Yang, Rui Yang, Xiuheng Liu, et al.
Annals of Surgical Oncology (2025)
Closed Access
Radiomics nomogram for preoperative prediction of progression-free survival using diffusion-weighted imaging in patients with muscle-invasive bladder cancer
Shenghai Zhang, Mengfan Song, Yuanshen Zhao, et al.
European Journal of Radiology (2020) Vol. 131, pp. 109219-109219
Closed Access | Times Cited: 30
A multiparametric MRI-based CAD system for accurate diagnosis of bladder cancer staging
Kamal Hammouda, Fahmi Khalifa, Ahmed Soliman, et al.
Computerized Medical Imaging and Graphics (2021) Vol. 90, pp. 101911-101911
Closed Access | Times Cited: 26
Integrating multiparametric MRI radiomics features and the Vesical Imaging-Reporting and Data System (VI-RADS) for bladder cancer grading
Zongtai Zheng, Feijia Xu, Zhuoran Gu, et al.
Abdominal Radiology (2021)
Closed Access | Times Cited: 26
On relevant features for the recurrence prediction of urothelial carcinoma of the bladder
Louisa Schwarz, Dominik Sobania, Franz Rothlauf
International Journal of Medical Informatics (2024) Vol. 186, pp. 105414-105414
Open Access | Times Cited: 3
Nomogram for predicting overall survival of patients with bladder cancer: A population-based study
Jiawu Wang, Xinyu Wu, Weiyang He, et al.
The International Journal of Biological Markers (2020) Vol. 35, Iss. 2, pp. 29-39
Open Access | Times Cited: 26
Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer
Zongtai Zheng, Zhuoran Gu, Feijia Xu, et al.
Cancer Imaging (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 23
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