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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:

Multiparametric MR radiomics in brain glioma: models comparation to predict biomarker status
Jinlong He, Jialiang Ren, Niu Guang-ming, et al.
BMC Medical Imaging (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 23

Showing 23 citing articles:

Clinical application of MR-Linac in tumor radiotherapy: a systematic review
Xin Liu, Zhenjiang Li, Yong Yin
Radiation Oncology (2023) Vol. 18, Iss. 1
Open Access | Times Cited: 23
Quality assessment of the MRI-radiomics studies for MGMT promoter methylation prediction in glioma: a systematic review and meta-analysis
Fabio Martino Doniselli, Riccardo Pascuzzo, Federica Mazzi, et al.
European Radiology (2024) Vol. 34, Iss. 9, pp. 5802-5815
Open Access | Times Cited: 9
Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis
Lanqing Li, Xiao Feng, Shouchao Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
AI tool for predicting MGMT methylation in glioblastoma for clinical decision support in resource limited settings
Felipe Cicci Farinha Restini, Tarraf Torfeh, Souha Aouadi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5
Virtual Biopsy for the Prediction of MGMT Promoter Methylation in Gliomas: A Comprehensive Review of Radiomics and Deep Learning Approaches Applied to MRI
Augusto Leone, Veronica Di Napoli, Nicola Pio Fochi, et al.
Diagnostics (2025) Vol. 15, Iss. 3, pp. 251-251
Open Access
Radiomics prediction of MGMT promoter methylation in adult diffuse gliomas: a combination of structural MRI, DCE, and DTI
Yuying Liu, Zhengyang Zhu, Jianan Zhou, et al.
Frontiers in Neurology (2025) Vol. 16
Open Access
Model incorporating multiple diffusion MRI features: development and validation of a radiomics-based model to predict adult-type diffuse gliomas grade
Peng Wang, Shenghui Xie, Qiong Wu, et al.
European Radiology (2023) Vol. 33, Iss. 12, pp. 8809-8820
Open Access | Times Cited: 9
Clinical Assessment of Magnetic Resonance Spectroscopy and Diffusion-Weighted Imaging in Diffuse Glioma: Insights Into Histological Grading and IDH Classification
Hanwen Zhang, Hongbo Zhang, Xiaolei Liu, et al.
Canadian Association of Radiologists Journal (2024)
Closed Access | Times Cited: 3
The current state of MRI-based radiomics in pituitary adenoma: promising but challenging
Baoping Zheng, Zhen Zhao, Pingping Zheng, et al.
Frontiers in Endocrinology (2024) Vol. 15
Open Access | Times Cited: 3
Combining Multi-Shell Diffusion with Conventional MRI Improves Molecular Diagnosis of Diffuse Gliomas with Deep Learning
Golestan Karami, Riccardo Pascuzzo, Matteo Figini, et al.
Cancers (2023) Vol. 15, Iss. 2, pp. 482-482
Open Access | Times Cited: 7
Amide proton transfer weighted and diffusion weighted imaging based radiomics classification algorithm for predicting 1p/19q co-deletion status in low grade gliomas
Andong Ma, X. Yan, Yaoming Qu, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 2
Advances in the Radiological Evaluation of and Theranostics for Glioblastoma
Grayson W. Hooper, Shehbaz Ansari, Jason M. Johnson, et al.
Cancers (2023) Vol. 15, Iss. 16, pp. 4162-4162
Open Access | Times Cited: 6
Identification of Radiomic Signatures in Brain MRI Sequences T1 and T2 That Differentiate Tumor Regions of Midline Gliomas with H3.3K27M Mutation
Maria-Fatima Chilaca-Rosas, Manuel-Tadeo Contreras-Aguilar, Melissa Garcia-Lezama, et al.
Diagnostics (2023) Vol. 13, Iss. 16, pp. 2669-2669
Open Access | Times Cited: 5
Radiomics for predicting MGMT status in cerebral glioblastoma: comparison of different MRI sequences
Fei Zheng, Lingling Zhang, Hongyan Chen, et al.
Journal of Radiation Research (2024) Vol. 65, Iss. 3, pp. 350-359
Open Access | Times Cited: 1
A radiomics‐based nomogram may be useful for predicting telomerase reverse transcriptase promoter mutation status in adult glioblastoma
Yao Li, Ling Chen, Lizhao Huang, et al.
Brain and Behavior (2024) Vol. 14, Iss. 5
Open Access | Times Cited: 1
Radiomics Analysis of Quantitative Maps from Synthetic MRI for Predicting Grades and Molecular Subtypes of Diffuse Gliomas
Danlin Lin, Jiehong Liu, Chao Ke, et al.
Clinical Neuroradiology (2024) Vol. 34, Iss. 4, pp. 817-826
Closed Access | Times Cited: 1
Dosiomics in the analysis of medical images and prospects for its use in clinical practice
V. А. Solodkiy, Nikolay V. Nudnov, Mikhail E. Ivannikov, et al.
Digital Diagnostics (2023) Vol. 4, Iss. 3, pp. 340-355
Open Access | Times Cited: 1
The Relationship Between the Molecular Phenotypes of Brain Gliomas and the Imaging Features and Sensitivity of Radiotherapy and Chemotherapy
Yulian Huang, Huiqing Fan, Youyi Kuang, et al.
Clinical Oncology (2024) Vol. 36, Iss. 9, pp. 541-551
Closed Access
Prediction of TERT mutation status in gliomas using conventional MRI radiogenomic features
Chuyun Tang, Ling Chen, Yifan Xu, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access
Predicting telomerase reverse transcriptase promoter mutation in glioma: A systematic review and diagnostic meta-analysis on machine learning algorithms
Mohammad Amin Habibi, Ali Dinpazhouh, Aliakbar Aliasgary, et al.
The Neuroradiology Journal (2024)
Open Access
The value of T2WI-based intratumoral and peritumoral edema radiomics in predicting IDH-1 genotype in gliomas
Wei Tang, Weixin Yang, Lei Tang, et al.
Research Square (Research Square) (2024)
Open Access
WITHDRAWN: The value of T2WI-based intratumoral and peritumoral edema radiomics in predicting IDH-1 genotype in gliomas
Wei Tang, Weixin Yang, Lei Tang, et al.
Research Square (Research Square) (2024)
Closed Access
Integrated analysis reveals the potential of cluster of differentiation 86 as a key biomarker in high-grade glioma
Xuebin Wen, Chaochao Wang, Zhihao Pan, et al.
Aging (2023)
Open Access
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