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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 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

Showing 1-25 of 27 citing articles:

Predicting muscle invasion in bladder cancer based on MRI: A comparison of radiomics, and single-task and multi-task deep learning
Jianpeng Li, Zhengxuan Qiu, Kangyang Cao, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 233, pp. 107466-107466
Closed Access | Times Cited: 27
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
Intratumoral and peritumoral CT-based radiomics for predicting the microsatellite instability in gastric cancer
Xingchi Chen, Zijian Zhuang, Lin Pen, et al.
Abdominal Radiology (2024) Vol. 49, Iss. 5, pp. 1363-1375
Closed Access | Times Cited: 6
Prediction of Ki-67 expression in bladder cancer based on CT radiomics nomogram
Shengxing Feng, Dongsheng Zhou, Yueming Li, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 5
Predicting muscle invasion in bladder cancer by deep learning analysis of MRI: comparison with vesical imaging–reporting and data system
Jianpeng Li, Kangyang Cao, Hongxin Lin, et al.
European Radiology (2022) Vol. 33, Iss. 4, pp. 2699-2709
Closed Access | Times Cited: 20
An automatic texture feature analysis framework of renal tumor: surgical, pathological, and molecular evaluation based on multi-phase abdominal CT
Huancheng Yang, Hanlin Liu, Jiashan Lin, et al.
European Radiology (2023) Vol. 34, Iss. 1, pp. 355-366
Closed Access | Times Cited: 11
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
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
An automated surgical decision-making framework for partial or radical nephrectomy based on 3D-CT multi-level anatomical features in renal cell carcinoma
Huancheng Yang, Kai Wu, Hanlin Liu, et al.
European Radiology (2023) Vol. 33, Iss. 11, pp. 7532-7541
Open Access | Times Cited: 9
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
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
CT-based deep learning radiomics signature for the preoperative prediction of the muscle-invasive status of bladder cancer
Weitian Chen, Mancheng Gong, Dongsheng Zhou, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 14
Radiomics for the Prediction of Overall Survival in Patients with Bladder Cancer Prior to Radical Cystectomy
Piotr Woźnicki, Fabian Christopher Laqua, Katharina Messmer, et al.
Cancers (2022) Vol. 14, Iss. 18, pp. 4449-4449
Open Access | Times Cited: 13
AI-powered radiomics: revolutionizing detection of urologic malignancies
David G. Gelikman, Soroush Rais‐Bahrami, Peter A. Pinto, et al.
Current Opinion in Urology (2023) Vol. 34, Iss. 1, pp. 1-7
Closed Access | Times Cited: 5
Can the Vesical Imaging Reporting and Data System (VI-RADS) score be applied in conventional ultrasound and contrast-enhanced ultrasound to differentiate muscle-invasive bladder cancer?
Ju Zhu, Xiao Huang, Luping Liu, et al.
Medical Ultrasonography (2023) Vol. 25, Iss. 1, pp. 22-22
Open Access | Times Cited: 4
Analysis of Bladder Cancer Staging Prediction Using Deep Residual Neural Network, Radiomics, and RNA-Seq from High-Definition CT Images
Yao Zhou, Xingju Zheng, Zhucheng Sun, et al.
Genetics Research (2024) Vol. 2024, pp. 1-11
Open Access | Times Cited: 1
Impact of virtual monochromatic images of different low-energy levels in dual-energy CT on radiomics models for predicting muscle invasion in bladder cancer
Mengting Hu, Wei Wei, Jingyi Zhang, et al.
Abdominal Radiology (2024) Vol. 49, Iss. 11, pp. 3883-3892
Closed Access | Times Cited: 1
Coupling Habitat Radiomic Analysis with the Diversification of the Tumor ecosystem: Illuminating New Strategy in the Assessment of Postoperative Recurrence of Non-Muscle Invasive Bladder Cancer
Hong Li, Yiqun Sui, Yongli Tao, et al.
Academic Radiology (2024) Vol. 32, Iss. 2, pp. 821-833
Closed Access | Times Cited: 1
Radiomics and Radiogenomics in Pelvic Oncology: Current Applications and Future Directions
Niall J. O’Sullivan, Michael E. Kelly
Current Oncology (2023) Vol. 30, Iss. 5, pp. 4936-4945
Open Access | Times Cited: 3
Value of the application of computed tomography‐based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer
Situ Xiong, Wentao Dong, Zhikang Deng, et al.
Cancer Medicine (2023) Vol. 12, Iss. 15, pp. 15868-15880
Open Access | Times Cited: 3
Multi-DECT image-based intratumoral and peritumoral radiomics for preoperative prediction of muscle invasion in bladder cancer
Mengting Hu, Jingyi Zhang, Qiye Cheng, et al.
Academic Radiology (2024)
Open Access
A New Approach to Predict the Histological Variants of Bladder Urothelial Carcinoma: Machine Learning-Based Radiomics Analysis
Muhammed Said Beşler, Ural Koç
Academic Radiology (2022) Vol. 29, Iss. 11, pp. 1690-1691
Closed Access | Times Cited: 2
Radiomics prediction of the pathological grade of bladder cancer based on multi-phase CT images
Jing Qian, Ling Yang, Su Hu, et al.
Research Square (Research Square) (2022)
Open Access | Times Cited: 1
CT-basierte Radiomics erkennen muskelinvasive Blasenkarzinome

Angewandte Nuklearmedizin (2023) Vol. 46, Iss. 02, pp. 100-100
Closed Access
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