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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:

Combining DWI radiomics features with transurethral resection promotes the differentiation between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer
Shuaishuai Xu, Qiuying Yao, Guiqin Liu, et al.
European Radiology (2019) Vol. 30, Iss. 3, pp. 1804-1812
Closed Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Quantitative Identification of Nonmuscle‐Invasive and Muscle‐Invasive Bladder Carcinomas: A Multiparametric MRI Radiomics Analysis
Xiaopan Xu, Xi Zhang, Qiang Tian, et al.
Journal of Magnetic Resonance Imaging (2018) Vol. 49, Iss. 5, pp. 1489-1498
Closed Access | Times Cited: 87
Use of Vesical Imaging-Reporting and Data System (VI-RADS) for detecting the muscle invasion of bladder cancer: a diagnostic meta-analysis
Cheng Luo, Bin Huang, Yukun Wu, et al.
European Radiology (2020) Vol. 30, Iss. 8, pp. 4606-4614
Closed Access | Times Cited: 82
Diagnosis and Staging of Bladder Cancer
Hamed Ahmadi, Vinay Duddalwar, Siamak Daneshmand
Hematology/Oncology Clinics of North America (2021) Vol. 35, Iss. 3, pp. 531-541
Closed Access | Times Cited: 68
Role of Radiomics in the Prediction of Muscle-invasive Bladder Cancer: A Systematic Review and Meta-analysis
Mieszko Kozikowski, Rodrigo Suarez-Ibarrola, Raúl Osiecki, et al.
European Urology Focus (2021) Vol. 8, Iss. 3, pp. 728-738
Closed Access | Times Cited: 57
CT-based radiomics to predict the pathological grade of bladder cancer
Gumuyang Zhang, Lili Xu, Lun Zhao, et al.
European Radiology (2020) Vol. 30, Iss. 12, pp. 6749-6756
Closed Access | Times Cited: 51
Automatic segmentation of bladder cancer on MRI using a convolutional neural network and reproducibility of radiomics features: a two-center study
Yusaku Moribata, Yasuhisa Kurata, Mizuho Nishio, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 17
Diffusion-weighted imaging-based radiomics model using automatic machine learning to differentiate cerebral cystic metastases from brain abscesses
Linyang Cui, Zheng Qin, Siyuan Sun, et al.
Journal of Cancer Research and Clinical Oncology (2024) Vol. 150, Iss. 3
Open Access | Times Cited: 7
Development and validation of a CT-based deep learning radiomics nomogram to predict muscle invasion in bladder cancer
Zongjie Wei, Huayun Liu, Yingjie Xv, et al.
Heliyon (2024) Vol. 10, Iss. 2, pp. e24878-e24878
Open Access | Times Cited: 6
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
Clinical utility of the Vesical Imaging-Reporting and Data System for muscle-invasive bladder cancer between radiologists and urologists based on multiparametric MRI including 3D FSE T2-weighted acquisitions
Yuki Arita, Keisuke Shigeta, Hirotaka Akita, et al.
European Radiology (2020) Vol. 31, Iss. 2, pp. 875-883
Open Access | Times Cited: 42
Deep Learning on Enhanced CT Images Can Predict the Muscular Invasiveness of Bladder Cancer
Gumuyang Zhang, Zhe Wu, Lili Xu, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 35
Radiomics in Oncology, Part 2: Thoracic, Genito-Urinary, Breast, Neurological, Hematologic and Musculoskeletal Applications
Damiano Caruso, Michela Polici, Marta Zerunian, et al.
Cancers (2021) Vol. 13, Iss. 11, pp. 2681-2681
Open Access | Times Cited: 34
Radiogenomics Map Reveals the Landscape of m6A Methylation Modification Pattern in Bladder Cancer
Fangdie Ye, Yun Hu, Jiahao Gao, et al.
Frontiers in Immunology (2021) Vol. 12
Open Access | Times Cited: 34
CT-based radiomics to predict muscle invasion in bladder cancer
Gumuyang Zhang, Zhe Wu, Xiaoxiao Zhang, et al.
European Radiology (2022) Vol. 32, Iss. 5, pp. 3260-3268
Closed Access | Times Cited: 27
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
Predicting preoperative muscle invasion status for bladder cancer using computed tomography-based radiomics nomogram
Rui Zhang, Shijun Jia, Linhan Zhai, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 4
Multi-path neural network based on mp-MRI for predicting muscle-invasive bladder cancer
Jie Yu, Lingkai Cai, Chunxiao Chen, et al.
Intelligent Data Analysis (2025)
Closed Access
Estimation of Ventricular and Intracranial Hemorrhage Volumes and Midline Shift on an External Validation Data Set Using a Convolutional Neural Network Algorithm
Marco Colasurdo, Dor Amran, Huanwen Chen, et al.
Neurosurgery (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
Usefulness of texture features of apparent diffusion coefficient maps in predicting chemoradiotherapy response in muscle-invasive bladder cancer
Koichiro Kimura, Soichiro Yoshida, Junichi Tsuchiya, et al.
European Radiology (2021) Vol. 32, Iss. 1, pp. 671-679
Closed Access | Times Cited: 24
Bladder Urothelial Carcinoma: Machine Learning-based Computed Tomography Radiomics for Prediction of Histological Variant
Şehnaz Evrimler, Mehmet Ali Gedik, T. Ahmet Serel, et al.
Academic Radiology (2022) Vol. 29, Iss. 11, pp. 1682-1689
Closed Access | Times Cited: 18
CT-based radiomics for the preoperative prediction of the muscle-invasive status of bladder cancer and comparison to radiologists' assessment
Yingpu Cui, Zepang Sun, X. Liu, et al.
Clinical Radiology (2022) Vol. 77, Iss. 6, pp. e473-e482
Closed Access | Times Cited: 17
A combined model based on CT radiomics and clinical variables to predict uric acid calculi which have a good accuracy
Zijie Wang, Guangjie Yang, Xinning Wang, et al.
Urolithiasis (2023) Vol. 51, Iss. 1
Open Access | Times Cited: 9
MRI‐Based Machine Learning Radiomics for Preoperative Assessment of Human Epidermal Growth Factor Receptor 2 Status in Urothelial Bladder Carcinoma
Ruixi Yu, Lingkai Cai, Yuxi Gong, et al.
Journal of Magnetic Resonance Imaging (2024) Vol. 60, Iss. 6, pp. 2694-2704
Closed Access | Times Cited: 3
The accuracy and quality of image-based artificial intelligence for muscle-invasive bladder cancer prediction
Chunlei He, Hui Xu, Enyu Yuan, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 3
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