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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:

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

Showing 20 citing articles:

Artificial Intelligence in the Advanced Diagnosis of Bladder Cancer-Comprehensive Literature Review and Future Advancement
Matteo Ferro, Ugo Giovanni Falagario, Biagio Barone, et al.
Diagnostics (2023) Vol. 13, Iss. 13, pp. 2308-2308
Open Access | Times Cited: 30
Recent trends in AI applications for pelvic MRI: a comprehensive review
Takahiro Tsuboyama, Masahiro Yanagawa, Tomoyuki Fujioka, et al.
La radiologia medica (2024) Vol. 129, Iss. 9, pp. 1275-1287
Closed Access | Times Cited: 5
A foundation model with weak experiential guidance in detecting muscle invasive bladder cancer on MRI
Yu Gong, Xiaodong Zhang, Yifan Xia, et al.
Cancer Letters (2025) Vol. 611, pp. 217438-217438
Closed Access
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
Multiparametric MRI for Bladder Cancer: A Practical Approach to the Clinical Application of VI-RADS
Martina Pecoraro, Stefano Cipollari, Emanuele Messina, et al.
Radiology (2025) Vol. 314, Iss. 3
Closed Access
Deep learning on T2WI to predict the muscle-invasive bladder cancer: a multi-center clinical study
Lingkai Cai, Xiao Yang, Jie Yu, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Optimizing bladder magnetic resonance imaging: accelerating scan time and improving image quality through deep learning
Er‐Jia Guo, Lixia Chen, Lili Xu, et al.
Abdominal Radiology (2025)
Closed Access
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
Multiparametric MRI‐Based Deep Learning Radiomics Model for Assessing 5‐Year Recurrence Risk in Non‐Muscle Invasive Bladder Cancer
Haolin Huang, Yiping Huang, Joshua Kaggie, et al.
Journal of Magnetic Resonance Imaging (2024)
Closed Access | Times Cited: 2
A multicenter bladder cancer MRI dataset and baseline evaluation of federated learning in clinical application
Kangyang Cao, Yujian Zou, Chang Zhang, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 2
VI-RADS for the diagnosis and management of urinary bladder cancer
Valeria Panebianco
European Radiology (2023) Vol. 33, Iss. 10, pp. 7209-7211
Open Access | Times Cited: 5
Radiomics Prediction of Muscle Invasion in Bladder Cancer Using Semi-Automatic Lesion Segmentation of MRI Compared with Manual Segmentation
Yaojiang Ye, Zixin Luo, Zhengxuan Qiu, et al.
Bioengineering (2023) Vol. 10, Iss. 12, pp. 1355-1355
Open Access | Times Cited: 4
A novel predict method for muscular invasion of bladder cancer based on 3D mp-MRI feature fusion
Jie Yu, Lingkai Cai, Chunxiao Chen, et al.
Physics in Medicine and Biology (2024) Vol. 69, Iss. 5, pp. 055011-055011
Closed Access | Times Cited: 1
Predicting intraoperative blood loss during cesarean sections based on multi-modal information: a two-center study
Changye Zheng, Peiyan Yue, Kangyang Cao, et al.
Abdominal Radiology (2024) Vol. 49, Iss. 7, pp. 2325-2339
Closed Access | Times Cited: 1
Development of deep learning model for diagnosing muscle-invasive bladder cancer on MRI with vision transformer
Yasuhisa Kurata, Mizuho Nishio, Yusaku Moribata, et al.
Heliyon (2024) Vol. 10, Iss. 16, pp. e36144-e36144
Open Access | Times Cited: 1
The role of MRI in muscle-invasive bladder cancer: an update from the last two years
Giovanni Luigi Pastorino, Chiara Mercinelli, Andrea Necchi
Current Opinion in Urology (2024)
Closed Access | Times Cited: 1
Prediction of muscular-invasive bladder cancer using multi-view fusion self-distillation model based on 3D T2-Weighted images
Yuan Zou, Jie Yu, Lingkai Cai, et al.
Biomedical Engineering / Biomedizinische Technik (2024)
Closed Access
Biomedical data analytics for better patient outcomes
Alireza Ghofrani, Hamed Taherdoost
Drug Discovery Today (2024), pp. 104280-104280
Closed Access
VI-RADS scoring system for predicting 1- to 5-year recurrence of bladder cancer
Athina C. Tsili
European Radiology (2023) Vol. 34, Iss. 5, pp. 3032-3033
Closed Access | Times Cited: 1
Personalized Prediction of Patient Radiation Exposure for Therapy of Urolithiasis: An Application and Comparison of Six Machine Learning Algorithms
Clemens Huettenbrink, Wolfgang Hitzl, Florian Distler, et al.
Journal of Personalized Medicine (2023) Vol. 13, Iss. 4, pp. 643-643
Open Access
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