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 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

Showing 17 citing articles:

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

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

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

The role of radiomics with machine learning in the prediction of muscle-invasive bladder cancer: A mini review
Xiaodan Huang, Xiangyu Wang, Xinxin Lan, 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

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

Radiomics vs radiologist in bladder and renal cancer. Results from a systematic review
Pietro Tramanzoli, Daniele Castellani, Virgilio De Stefano, et al.
Editor-in-Chief s Voice List of Authors is an Important Element in a Scientific Publication (2023)
Open Access | Times Cited: 5

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

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

Prognostic predictive value of urothelial carcinoma of the bladder after TURBT based on multiphase CT radiomics
Jing Xue, Zijian Zhuang, Lin Peng, et al.
Abdominal Radiology (2024) Vol. 49, Iss. 6, pp. 1975-1986
Closed Access

Textual Analysis of CT and MR images in bladder cancer: The promise and pitfalls in systematic review
A. A. Kovalenko, В. Е. Синицын, Victor Petrovichev
Digital Diagnostics (2024)
Open Access

Precise vesical wall staging of bladder cancer in the era of precision medicine: has it been fulfilled?
Mohamed Ragab Nouh, Omnia Ezz Eldin
Abdominal Radiology (2024)
Closed 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

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