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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:

A Review of Radiomics and Deep Predictive Modeling in Glioma Characterization
Sonal Gore, Tanay Chougule, Jayant Jagtap, et al.
Academic Radiology (2020) Vol. 28, Iss. 11, pp. 1599-1621
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Radiomics and radiogenomics in gliomas: a contemporary update
Gagandeep Singh, Sunil Manjila, Nicole Sakla, et al.
British Journal of Cancer (2021) Vol. 125, Iss. 5, pp. 641-657
Open Access | Times Cited: 159
Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning
Sebastian R. van der Voort, Fatih Incekara, Maarten M.J. Wijnenga, et al.
Neuro-Oncology (2022) Vol. 25, Iss. 2, pp. 279-289
Open Access | Times Cited: 82
Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging
Ahmed Abdel Khalek Abdel Razek, Ahmed Alksas, Mohamed Shehata, et al.
Insights into Imaging (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 96
Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors
Wynton B. Overcast, Korbin M. Davis, Chang Yueh Ho, et al.
Current Oncology Reports (2021) Vol. 23, Iss. 3
Open Access | Times Cited: 83
Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients
Jing Yan, Bin Zhang, Shuaitong Zhang, et al.
npj Precision Oncology (2021) Vol. 5, Iss. 1
Open Access | Times Cited: 74
A deep learning framework integrating MRI image preprocessing methods for brain tumor segmentation and classification
Thi Thu Khiet Dang, Vo Van Toi, Lua Ngo, et al.
IBRO Neuroscience Reports (2022) Vol. 13, pp. 523-532
Open Access | Times Cited: 38
Predictive Modeling in Medicine
Milan Toma, Chi Wei Ong
Encyclopedia (2023) Vol. 3, Iss. 2, pp. 590-601
Open Access | Times Cited: 37
Recapitulating the Key Advances in the Diagnosis and Prognosis of High-Grade Gliomas: Second Half of 2021 Update
Guido Fròsina
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 7, pp. 6375-6375
Open Access | Times Cited: 21
A Pipeline for the Implementation and Visualization of Explainable Machine Learning for Medical Imaging Using Radiomics Features
Cameron Severn, Krithika Suresh, Carsten Görg, et al.
Sensors (2022) Vol. 22, Iss. 14, pp. 5205-5205
Open Access | Times Cited: 33
Neuroprotective Potential of Aromatic Herbs: Rosemary, Sage, and Lavender
Arezoo Faridzadeh, Yasaman Salimi, Hamidreza Ghasemirad, et al.
Frontiers in Neuroscience (2022) Vol. 16
Open Access | Times Cited: 30
Treatment Response and Prognosis Evaluation in High‐Grade Glioma: An Imaging Review Based on MRI
Qing Zhou, Caiqiang Xue, Xiaoai Ke, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 56, Iss. 2, pp. 325-340
Closed Access | Times Cited: 27
Time-to-event overall survival prediction in glioblastoma multiforme patients using magnetic resonance imaging radiomics
Ghasem Hajianfar, Atlas Haddadi Avval, Seyyed Ali Hosseini, et al.
La radiologia medica (2023) Vol. 128, Iss. 12, pp. 1521-1534
Open Access | Times Cited: 18
Grading diffuse glioma based on 2021 WHO grade using self-attention-base deep learning architecture: variable Vision Transformer (vViT)
Takuma Usuzaki, Kengo Takahashi, Ryusei Inamori, et al.
Biomedical Signal Processing and Control (2024) Vol. 91, pp. 106001-106001
Open Access | Times Cited: 6
Radiomics in glioma: emerging trends and challenges
Zihan Wang, Lei Wang, Yinyan Wang
Annals of Clinical and Translational Neurology (2025)
Open Access
Radiomics model building from multiparametric MRI to predict Ki-67 expression in patients with primary central nervous system lymphomas: a multicenter study
Yelong Shen, Siyu Wu, Yanan Wu, et al.
BMC Medical Imaging (2025) Vol. 25, Iss. 1
Open Access
EFNB1 drives glioma progression and shapes the immune microenvironment: a potential prognostic biomarker
Yungui Zheng, Jinpeng Shi
Discover Oncology (2025) Vol. 16, Iss. 1
Open Access
Characterizing the molecular and spatial heterogeneity of midline gliomas in adults: a single institution analysis
Bryan J. Neth, Robert M. Kraft, Kathryn L. Eschbacher, et al.
Journal of Neuro-Oncology (2025)
Closed Access
Artificial intelligence in paediatric radiology: Future opportunities
Natasha Davendralingam, Neil J. Sebire, Owen J. Arthurs, et al.
British Journal of Radiology (2020) Vol. 94, Iss. 1117
Open Access | Times Cited: 41
Deep Learning Aided Neuroimaging and Brain Regulation
Mengze Xu, Yuanyuan Ouyang, Zhen Yuan
Sensors (2023) Vol. 23, Iss. 11, pp. 4993-4993
Open Access | Times Cited: 15
Advances on Liquid Biopsy Analysis for Glioma Diagnosis
Panagiotis Skouras, Mariam Markouli, Theodosis Κalamatianos, et al.
Biomedicines (2023) Vol. 11, Iss. 9, pp. 2371-2371
Open Access | Times Cited: 14
Advancing glioma diagnosis: Integrating custom U-Net and VGG-16 for improved grading in MR imaging
Sonam Saluja, Munesh Chandra Trivedi, S. S. Sarangdevot
Mathematical Biosciences & Engineering (2024) Vol. 21, Iss. 3, pp. 4328-4350
Open Access | Times Cited: 4
Challenges and opportunities for artificial intelligence in oncological imaging
Helen Cheung, Daniel L. Rubin
Clinical Radiology (2021) Vol. 76, Iss. 10, pp. 728-736
Open Access | Times Cited: 27
Preoperative Diagnosis and Molecular Characterization of Gliomas With Liquid Biopsy and Radiogenomics
Carmen Balañá, Sara Castañer, Cristina Carrato, et al.
Frontiers in Neurology (2022) Vol. 13
Open Access | Times Cited: 20
Application of Artificial Intelligence Methods for Imaging of Spinal Metastasis
Wilson Ong, Lei Zhu, Wenqiao Zhang, et al.
Cancers (2022) Vol. 14, Iss. 16, pp. 4025-4025
Open Access | Times Cited: 20
Machine-Learning and Radiomics-Based Preoperative Prediction of Ki-67 Expression in Glioma Using MRI Data
Jiaying Ni, Hongjian Zhang, Qing Yang, et al.
Academic Radiology (2024) Vol. 31, Iss. 8, pp. 3397-3405
Closed Access | Times Cited: 3
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