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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:

Comprehensive Genomic Subtyping of Glioma Using Semi-Supervised Multi-Task Deep Learning on Multimodal MRI
Priyanka Tupe-Waghmare, Piyush Malpure, Ketan Kotecha, et al.
IEEE Access (2021) Vol. 9, pp. 167900-167910
Open Access | Times Cited: 15

Showing 15 citing articles:

A scoping review of interpretability and explainability concerning artificial intelligence methods in medical imaging
Mélanie Champendal, Henning Müller, John O. Prior, et al.
European Journal of Radiology (2023) Vol. 169, pp. 111159-111159
Open Access | Times Cited: 16
Diagnostic Accuracy of Deep Learning Models in Predicting Glioma Molecular Markers: A Systematic Review and Meta-Analysis
Somayeh Farahani, Marjaneh Hejazi, Sahar Moradizeyveh, et al.
Diagnostics (2025) Vol. 15, Iss. 7, pp. 797-797
Open Access
A Clustering-based Hybrid Approach for Analyzing High-grade Gliomas Using Radiomic Features
V. A. Sairam, Navaneeth Bhaskar, Priyanka Tupe-Waghmare
Pertanika journal of science & technology (2025) Vol. 33, Iss. 3
Closed Access
Design of Transfer Learning based Deep CNN Paradigm for Brain Tumor Classification
Neha Bhardwaj, Meenakshi Sood, SS Gill
WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE (2024) Vol. 21, pp. 162-169
Open Access | Times Cited: 2
Multi-modal fusion deep transfer learning for accurate brain tumor classification using magnetic resonance imaging images
Srinivas Babu Gottipati, T. Gowri
Indonesian Journal of Electrical Engineering and Computer Science (2024) Vol. 34, Iss. 2, pp. 825-825
Open Access | Times Cited: 1
A Deep Learning Hybrid Approach for Automated Leaf Disease Identification in Paddy Crops
Navaneeth Bhaskar, Pratiksha Churya A, Priyanka Tupe-Waghmare, et al.
(2024), pp. 1-5
Closed Access | Times Cited: 1
Artificial Intelligence Applications in Glioma With 1p/19q Co‐Deletion: A Systematic Review
Simin Zhang, Lijuan Yin, Lu Ma, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 58, Iss. 5, pp. 1338-1352
Closed Access | Times Cited: 4
External Validation of a Convolutional Neural Network for IDH Mutation Prediction
Iona Hrapșa, Ioan Alexandru Florian, Sergiu Șușman, et al.
Medicina (2022) Vol. 58, Iss. 4, pp. 526-526
Open Access | Times Cited: 7
Multi-task learning based on geometric invariance discriminative features
Yitong Liu, Lei Huang, Jie Li, et al.
Applied Intelligence (2022) Vol. 53, Iss. 3, pp. 3505-3518
Closed Access | Times Cited: 6
Bibliometric research on the developments of artificial intelligence in radiomics toward nervous system diseases
Jiangli Cui, Xingyu Miao, Xiaoyu Yanghao, et al.
Frontiers in Neurology (2023) Vol. 14
Open Access | Times Cited: 3
A Novel Attention-Based Multi-Modal Modeling Technique on Mixed Type Data for Improving TFT-LCD Repair Process
Yi Liu, Hsueh-Ping Lu, Ching-Hao Lai
IEEE Access (2022) Vol. 10, pp. 33026-33036
Open Access | Times Cited: 3
Design and Development of Hypertuned Deep learning Frameworks for Detection and Severity Grading of Brain Tumor using Medical Brain MR images
Neha Bhardwaj, Meenakshi Sood, Sandeep Singh Gill
Current Medical Imaging Formerly Current Medical Imaging Reviews (2024) Vol. 20
Open Access
Empirical perspectives on machine learning models for contextual analysis of MRI scans
Swati K. Mohod, Rajesh Thakare
AIP conference proceedings (2024) Vol. 3188, pp. 090005-090005
Closed Access
An efficient convolutional neural network-extreme gradient boosting hybrid deep learning model for disease detection applications
Navaneeth Bhaskar, Aswathy Maruthompilli Ajithkumar, Priyanka Tupe-Waghmare
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2024) Vol. 14, Iss. 2, pp. 2035-2035
Open Access
A Multi-task CNN Model for Automated Prediction of Isocitrate Dehydrogenase Mutation Status and Grade of Gliomas
Priyanka Tupe-Waghmare, V. A. Sairam, Navaneeth Bhaskar
Mathematical Modelling and Engineering Problems (2024) Vol. 11, Iss. 5, pp. 1198-1206
Open Access
Automated Glioma Grading and IDH Mutation Status Prediction Using CNN-Based Deep Learning Models
V. A. Sairam, Navaneeth Bhaskar, Priyanka Tupe-Waghmare
Lecture notes in electrical engineering (2024), pp. 391-400
Closed Access
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