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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:

Deep learning–based radiomic nomograms for predicting Ki67 expression in prostate cancer
Shuitang Deng, Jingfeng Ding, Hui Wang, et al.
BMC Cancer (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 13

Showing 13 citing articles:

Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment
Chaoyi Zhang, Jin Xu, Rong Tang, et al.
Journal of Hematology & Oncology (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 49
Integrating Omics Data and AI for Cancer Diagnosis and Prognosis
Y. Ozaki, P M Broughton, Hamed Abdollahi, et al.
Cancers (2024) Vol. 16, Iss. 13, pp. 2448-2448
Open Access | Times Cited: 12
Integrating Omics Data and AI for Cancer Diagnosis and Prognosis: A Systematic Review
Yousaku Ozaki, P M Broughton, Hamed Abdollahi, et al.
(2024)
Open Access | Times Cited: 5
Deep Learning Algorithm‑Based MRI Radiomics and Pathomics for Predicting Microsatellite Instability Status in Rectal Cancer: A Multicenter Study
Xiuzhen Yao, Shuitang Deng, Xiaoyu Han, et al.
Academic Radiology (2024)
Closed Access | Times Cited: 4
Development and Validation of MRI Radiomics Model for Predicting Perineural Invasion in Rectal Cancer
Zhengyu Cao, Tiejun Yang, Wanfeng Gong, et al.
Research Square (Research Square) (2025)
Closed Access
Novel deep learning algorithm based MRI radiomics for predicting lymph node metastases in rectal cancer
Weiqun Ao, Sikai Wu, Neng Wang, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Development and verification of a radiomics model to forecast Ki67 index and prognosis in advanced gastric tubular adenocarcinoma
Jiatong Lu, Yong Xiao, Qiushuang Wang, et al.
BMC Gastroenterology (2025) Vol. 25, Iss. 1
Open Access
Can Habitat-Based MRI Radiomics Distinguish Between T2 and T3 Stages in Rectal Cancer?
Weiqun Ao, Sikai Wu, Guoqun Mao, et al.
Academic Radiology (2025)
Closed Access
Preoperative prediction of Ki-67 expression in medullary thyroid carcinoma based on ultrasonographic features: a 10-year retrospective study
Qianru Zhang, Yan Hu, X. R. Chen, et al.
European Journal of Radiology (2025), pp. 112134-112134
Closed Access
MRI radiomics-based interpretable model and nomogram for preoperative prediction of Ki-67 expression status in primary central nervous system lymphoma
Endong Zhao, Yunfeng Yang, Miaomiao Bai, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 3
Deep learning-based multi-parametric magnetic resonance imaging (mp-MRI) nomogram for predicting Ki-67 expression in rectal cancer
Sikai Wu, Neng Wang, Weiqun Ao, et al.
Abdominal Radiology (2024) Vol. 49, Iss. 9, pp. 3003-3014
Closed Access | Times Cited: 1
Prostate Cancer: MRI Image Detection Based on Deep Learning: A Review
Jelan Salih Jasim Alhamzo, Adnan Mohsin Abdulazeez
Indonesian Journal of Computer Science (2024) Vol. 13, Iss. 3
Open Access
Multiparametric MRI-Based Deep Learning Models for Preoperative Prediction of Tumor Deposits in Rectal Cancer and Prognostic Outcome
Weiqun Ao, Neng Wang, Xu Chen, et al.
Academic Radiology (2024)
Closed Access
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