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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 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

Showing 1-25 of 51 citing articles:

Performing Automatic Identification and Staging of Urothelial Carcinoma in Bladder Cancer Patients Using a Hybrid Deep-Machine Learning Approach
Suryadipto Sarkar, Kong Min, Waleed Ikram, et al.
Cancers (2023) Vol. 15, Iss. 6, pp. 1673-1673
Open Access | Times Cited: 23
Emerging Trends in AI and Radiomics for Bladder, Kidney, and Prostate Cancer: A Critical Review
Georgios Feretzakis, Patrick Juliebø‐Jones, Arman Tsaturyan, et al.
Cancers (2024) Vol. 16, Iss. 4, pp. 810-810
Open Access | Times Cited: 12
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
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
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
Prediction Model of Hemorrhage Transformation in Patient with Acute Ischemic Stroke Based on Multiparametric MRI Radiomics and Machine Learning
Yucong Meng, Haoran Wang, Chuanfu Wu, et al.
Brain Sciences (2022) Vol. 12, Iss. 7, pp. 858-858
Open Access | Times Cited: 26
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
CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study
Hongzheng Song, Shifeng Yang, Boyang Yu, et al.
Cancer Imaging (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 12
A computed tomography urography‐based machine learning model for predicting preoperative pathological grade of upper urinary tract urothelial carcinoma
Yanghuang Zheng, Hongjin Shi, Shi Fu, et al.
Cancer Medicine (2024) Vol. 13, Iss. 1
Open Access | Times Cited: 4
A CT-based deep learning model predicts overall survival in patients with muscle invasive bladder cancer after radical cystectomy: a multicenter retrospective cohort study
Zongjie Wei, Yingjie Xv, Huayun Liu, et al.
International Journal of Surgery (2024)
Open Access | Times Cited: 4
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
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
Predicting Drug Treatment Outcomes in Children with Tuberous Sclerosis Complex–Related Epilepsy: A Clinical Radiomics Study
Zhanqi Hu, Dian Jiang, Xia Zhao, et al.
American Journal of Neuroradiology (2023) Vol. 44, Iss. 7, pp. 853-860
Open Access | Times Cited: 10
Machine learning models combining computed tomography semantic features and selected clinical variables for accurate prediction of the pathological grade of bladder cancer
Zhikang Deng, Wentao Dong, Situ Xiong, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 9
The Role of 18F-FDG PET/CT in Guiding Precision Medicine for Invasive Bladder Carcinoma
Antoine Girard, Helena Vila-Reyes, Hiram Shaish, et al.
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 24
A Potential Prognostic Marker for Recognizing VEGF-Positive Hepatocellular Carcinoma Based on Magnetic Resonance Radiomics Signature
Tingting Fan, Shijie Li, Kai Li, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 15
A CT-Based Radiomics Nomogram Combined with Clinic-Radiological Characteristics for Preoperative Prediction of the Novel IASLC Grading of Invasive Pulmonary Adenocarcinoma
Zhihe Yang, Yuqin Cai, Yirong Chen, et al.
Academic Radiology (2022) Vol. 30, Iss. 9, pp. 1946-1961
Open Access | Times Cited: 15
Feasibility Study on Predicting Recurrence Risk of Bladder Cancer Based on Radiomics Features of Multiphase CT Images
Jing Qian, Ling Yang, Su Hu, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 14
A CT-Based Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperatively Predicting WHO/ISUP Grade of Clear Cell Renal Cell Carcinoma
Yingjie Xv, Fajin Lv, Haoming Guo, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 19
Systematic radiomics analysis based on multiparameter MRI to preoperatively predict the expression of Ki67 and histological grade in patients with bladder cancer
Xuhui Fan, Hongwei Yu, Ni Xie, et al.
British Journal of Radiology (2023) Vol. 96, Iss. 1145
Closed Access | Times Cited: 7
Study Progress of Noninvasive Imaging and Radiomics for Decoding the Phenotypes and Recurrence Risk of Bladder Cancer
Xiaopan Xu, Huanjun Wang, Yan Guo, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 17
Discriminating Between Benign and Malignant Solid Ovarian Tumors Based on Clinical and Radiomic Features of MRI
Yuemei Zheng, Hong Wang, Qiong Li, et al.
Academic Radiology (2022) Vol. 30, Iss. 5, pp. 814-822
Closed Access | Times Cited: 12
Clinical-radiomics nomogram using contrast-enhanced CT to predict histological grade and survival in pancreatic ductal adenocarcinoma
Chunyuan Cen, Chunyou Wang, Siqi Wang, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 6
Radiomics Signature Using Manual Versus Automated Segmentation for Lymph Node Staging of Bladder Cancer
Eva Gresser, Piotr Woźnicki, Katharina Messmer, et al.
European Urology Focus (2022) Vol. 9, Iss. 1, pp. 145-153
Closed Access | Times Cited: 10
Predicting Recurrence of Non-Muscle-Invasive Bladder Cancer: Current Techniques and Future Trends
Aya T. Shalata, Mohamed Shehata, Eric Van Bogaert, et al.
Cancers (2022) Vol. 14, Iss. 20, pp. 5019-5019
Open Access | Times Cited: 9
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