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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:

Machine Learning and Radiomic Features to Predict Overall Survival Time for Glioblastoma Patients
Lina Chato, Shahram Latifi
Journal of Personalized Medicine (2021) Vol. 11, Iss. 12, pp. 1336-1336
Open Access | Times Cited: 15

Showing 15 citing articles:

A transfer learning approach on MRI-based radiomics signature for overall survival prediction of low-grade and high-grade gliomas
Viet Huan Le, Tran Nguyen Tuan Minh, Quang Hien Kha, et al.
Medical & Biological Engineering & Computing (2023) Vol. 61, Iss. 10, pp. 2699-2712
Closed Access | Times Cited: 18
Prediction of O-6-methylguanine-DNA methyltransferase and overall survival of the patients suffering from glioblastoma using MRI-based hybrid radiomics signatures in machine and deep learning framework
Sanjay Saxena, Aaditya Agrawal, Pankaj Kumar, et al.
Neural Computing and Applications (2023) Vol. 35, Iss. 18, pp. 13647-13663
Closed Access | Times Cited: 17
Prediction of Survival of Glioblastoma Patients Using Local Spatial Relationships and Global Structure Awareness in FLAIR MRI Brain Images
Minh-Trieu Tran, Hyung-Jeong Yang, Soo-Hyung Kim, et al.
IEEE Access (2023) Vol. 11, pp. 37437-37449
Open Access | Times Cited: 13
Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data
Lina Chato, Emma Regentova
Journal of Personalized Medicine (2023) Vol. 13, Iss. 12, pp. 1703-1703
Open Access | Times Cited: 13
Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI
Christian di Noia, James T. Grist, Frank Riemer, et al.
Diagnostics (2022) Vol. 12, Iss. 9, pp. 2125-2125
Open Access | Times Cited: 12
Risk Stratification and Overall Survival Prediction in Advanced Gastric Cancer Patients Based on Whole‐Volume MRI Radiomics
Wujie Chen, Chen Gao, Can Hu, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 58, Iss. 4, pp. 1161-1174
Open Access | Times Cited: 6
Forecasting Molecular Features in IDH-Wildtype Gliomas: The State of the Art of Radiomics Applied to Neurosurgery
Rosa Maria Gerardi, Roberto Cannella, Lapo Bonosi, et al.
Cancers (2023) Vol. 15, Iss. 3, pp. 940-940
Open Access | Times Cited: 4
Deep synergetic spiking neural P systems for the overall survival time prediction of glioblastoma patients
Xiu Yin, Xiyu Liu, Jinpeng Dai, et al.
Expert Systems with Applications (2023) Vol. 245, pp. 123032-123032
Closed Access | Times Cited: 4
An Experimental Study Using Deep Neural Networks to Predict the Recurrence Risk of Brain Tumor Glioblastoma Multiform
Chetan J. Shelke Disha Sushant Wankhede
Deleted Journal (2024) Vol. 20, Iss. 1s, pp. 498-507
Open Access | Times Cited: 1
Uses of artificial intelligence in glioma: A systematic review
Adham Al-Rahbi, Omar Al-Mahrouqi, Tariq Al‐Saadi
Medicine International (2024) Vol. 4, Iss. 4
Open Access | Times Cited: 1
Survival prediction of glioblastoma patients using machine learning and deep learning: a systematic review
Roya Poursaeed, Mohsen Mohammadzadeh, Ali Asghar Safaei
BMC Cancer (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Relevance maps: A weakly supervised segmentation method for 3D brain tumours in MRIs
Sajith Rajapaksa, Farzad Khalvati
Frontiers in Radiology (2022) Vol. 2
Open Access | Times Cited: 4
Survival estimation of brain tumor patients using radiogenomics-based studies
Soumyaranjan Panda, K.P. Padhi, K. Behera, et al.
Elsevier eBooks (2024), pp. 137-166
Closed Access
An image-based modeling framework for predicting spatiotemporal brain cancer biology within individual patients
Kamila M. Bond, Lee Curtin, Sara Ranjbar, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 1
Experimental Evaluation of Brain Tumor Image Segmentation and Detection Using CNN Model
Debjit Koner, Soumya Ranjan Sahoo
Studies in computational intelligence (2022), pp. 103-119
Closed Access
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