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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:

Preoperative prediction and histological stratification of intracranial solitary fibrous tumours by machine-learning models
Xiaopeng Kong, Yong Luo, Y. Li, et al.
Clinical Radiology (2022) Vol. 78, Iss. 3, pp. e204-e213
Closed Access | Times Cited: 9

Showing 9 citing articles:

Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions
Mohamed Khalifa, Mona Albadawy
Computer Methods and Programs in Biomedicine Update (2024) Vol. 5, pp. 100148-100148
Open Access | Times Cited: 43
A novel rotation and scale-invariant deep learning framework leveraging conical transformers for precise differentiation between meningioma and solitary fibrous tumor
Mohamed T. Azam, Hossam Magdy Balaha, Akshitkumar M. Mistry, et al.
Journal of Pathology Informatics (2025) Vol. 17, pp. 100422-100422
Open Access
Development of an MRI‐Based Comprehensive Model Fusing Clinical, Radiomics and Deep Learning Models for Preoperative Histological Stratification in Intracranial Solitary Fibrous Tumor
Xiaohong Liang, Kaiqiang Tang, Xiaoai Ke, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 60, Iss. 2, pp. 523-533
Closed Access | Times Cited: 4
A Novel Vit-Based Multi-Scaled and Rotation-Invariance Approach for Precise Differentiation Between Meningioma and Solitary Fibrous Tumor
Mohamed T. Azam, Hossam Magdy Balaha, Khadiga M. Ali, et al.
(2024), pp. 1-4
Closed Access | Times Cited: 1
Preoperative MRI-based radiomic nomogram for distinguishing solitary fibrous tumor from angiomatous meningioma: a multicenter study
Mengjie Li, Shengli Fu, Jingjing Du, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 1
Nomograms Based on MRI Radiomics for Differential Diagnosis and Predicting BRAFV600E Expression in Pleomorphic Xanthoastrocytoma and Ganglioglioma
Xin Kong, Yu M, Fengjun Xi, et al.
Academic Radiology (2023) Vol. 31, Iss. 3, pp. 1069-1081
Closed Access | Times Cited: 2
Deep learning radiomic nomogram outperforms the clinical model in distinguishing intracranial solitary fibrous tumors from angiomatous meningiomas and can predict patient prognosis
Xiaohong Liang, Xiaoai Ke, Wanjun Hu, et al.
European Radiology (2024)
Closed Access
Prognostic significance of collagen content in solitary fibrous tumors of the central nervous system
Xiaoling Li, Han Zhang, Chengcong Hu, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access
Histopathological Diagnosis of Meningioma and Solitary Fibrous Tumors Based on a Multi-scale Fusion Approach Utilizing Vision Transformer and Texture Analysis
Mohamed T. Azam, Hossam Magdy Balaha, Dibson Gondim, et al.
Lecture notes in computer science (2024), pp. 31-45
Closed Access
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