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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:

Development of a noninvasive tool to preoperatively evaluate the muscular invasiveness of bladder cancer using a radiomics approach
Junjiong Zheng, Jianqiu Kong, Shaoxu Wu, et al.
Cancer (2019) Vol. 125, Iss. 24, pp. 4388-4398
Open Access | Times Cited: 69

Showing 26-50 of 69 citing articles:

Artificial intelligence in urological oncology: An update and future applications
Andrew Brodie, Nick Dai, Jeremy Yuen‐Chun Teoh, et al.
Urologic Oncology Seminars and Original Investigations (2021) Vol. 39, Iss. 7, pp. 379-399
Closed Access | Times Cited: 25
Differentiation of testicular seminomas from nonseminomas based on multiphase CT radiomics combined with machine learning: A multicenter study
Fuxiang Fang, Linfeng Wu, Xing Luo, et al.
European Journal of Radiology (2024) Vol. 175, pp. 111416-111416
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
Radiomic features of magnetic resonance images as novel preoperative predictive factors of bone invasion in meningiomas
Jing Zhang, Jianqing Sun, Tao Han, et al.
European Journal of Radiology (2020) Vol. 132, pp. 109287-109287
Closed Access | Times Cited: 27
Magnetic resonance imaging-based radiomics signature for preoperative prediction of Ki67 expression in bladder cancer
Zongtai Zheng, Zhuoran Gu, Feijia Xu, et al.
Cancer Imaging (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 23
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
MRI-Based Radiomics in Bladder Cancer: A Systematic Review and Radiomics Quality Score Assessment
Bianca Boca, Cosmin Caraiani, Teodora Telecan, et al.
Diagnostics (2023) Vol. 13, Iss. 13, pp. 2300-2300
Open Access | Times Cited: 8
MRI-based automated machine learning model for preoperative identification of variant histology in muscle-invasive bladder carcinoma
Jingwen Huang, Guanxing Chen, Haiqing Liu, et al.
European Radiology (2023) Vol. 34, Iss. 3, pp. 1804-1815
Closed Access | Times Cited: 8
Non-Invasive Radiomics Approach Predict Invasiveness of Adamantinomatous Craniopharyngioma Before Surgery
Guofo Ma, Jie Kang, Ning Qiao, et al.
Frontiers in Oncology (2021) Vol. 10
Open Access | Times Cited: 20
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
Identifying ureteral stent encrustation using machine learning based on CT radiomics features: a bicentric study
Junliang Qiu, Bo Yan, Haojie Wang, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 7
Deep-learning-based 3D super-resolution CT radiomics model: Predict the possibility of the micropapillary/solid component of lung adenocarcinoma
Xiaowei Xing, Liangping Li, Mingxia Sun, et al.
Heliyon (2024) Vol. 10, Iss. 13, pp. e34163-e34163
Open Access | Times Cited: 2
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
Multi‐Sequence and Multi‐Regional MRI‐Based Radiomics Nomogram for the Preoperative Assessment of Muscle Invasion in Bladder Cancer
Lu Zhang, Xiaoyang Li, Li Yang, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 58, Iss. 1, pp. 258-269
Closed Access | Times Cited: 12
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
Applications of radiomics in genitourinary tumors.
Longfei Liu, Xiaoping Yi, Can Lü, et al.
PubMed (2020) Vol. 10, Iss. 8, pp. 2293-2308
Closed Access | Times Cited: 15
Virtual biopsy in abdominal pathology: where do we stand?
Arianna Defeudis, Jovana Panić, Giulia Nicoletti, et al.
BJR|Open (2023) Vol. 5, Iss. 1
Open Access | Times Cited: 5
Nomogram Based on Super-Resolution Ultrasound Images Outperforms in Predicting Benign and Malignant Breast Lesions
Liu Yang, Zhe Ma
Breast Cancer Targets and Therapy (2023) Vol. Volume 15, pp. 867-878
Open Access | Times Cited: 5
Multimodality Imaging and Artificial Intelligence for Tumor Characterization: Current Status and Future Perspective
Jérémy Dana, Vincent Agnus, Farid Ouhmich, et al.
Seminars in Nuclear Medicine (2020) Vol. 50, Iss. 6, pp. 541-548
Open Access | Times Cited: 14
Nomograms for predicting long-term overall survival and cancer-specific survival in patients with primary urethral carcinoma: a population-based study
Hao Zi, Lei Gao, Zhao-Hua Yu, et al.
International Urology and Nephrology (2019) Vol. 52, Iss. 2, pp. 287-300
Closed Access | Times Cited: 12
New Challenges in Bladder Cancer Diagnosis: How Biosensing Tools Can Lead to Population Screening Opportunities
Fabiana Tortora, Antonella Guastaferro, Simona Barbato, et al.
Sensors (2024) Vol. 24, Iss. 24, pp. 7873-7873
Open Access | Times Cited: 1
Association of chromosome 7 aneuploidy measured by fluorescence in situ hybridization assay with muscular invasion in bladder cancer
Xiayao Diao, Jinhua Cai, Junjiong Zheng, et al.
Cancer Communications (2020) Vol. 40, Iss. 4, pp. 167-180
Open Access | Times Cited: 11
Radiomics and Bladder Cancer: Current Status
Giovanni Cacciamani, Nima Nassiri, Bino Varghese, et al.
Bladder Cancer (2020) Vol. 6, Iss. 3, pp. 343-362
Closed Access | Times Cited: 9
Radiomics Analysis Based on Ultrasound Images to Distinguish the Tumor Stage and Pathological Grade of Bladder Cancer
Ruizhi Gao, Rong Wen, Dong‐yue Wen, et al.
Journal of Ultrasound in Medicine (2021) Vol. 40, Iss. 12, pp. 2685-2697
Closed Access | Times Cited: 9
Refining neoadjuvant therapy clinical trial design for muscle-invasive bladder cancer before cystectomy: a joint US Food and Drug Administration and Bladder Cancer Advocacy Network workshop
Elaine Chang, Andrea B. Apolo, Rick Bangs, et al.
Nature Reviews Urology (2021) Vol. 19, Iss. 1, pp. 37-46
Closed Access | Times Cited: 9

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