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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:

Multimodal 3D DenseNet for IDH Genotype Prediction in Gliomas
Sen Liang, Rongguo Zhang, Dayang Liang, et al.
Genes (2018) Vol. 9, Iss. 8, pp. 382-382
Open Access | Times Cited: 113

Showing 1-25 of 113 citing articles:

Transfer learning techniques for medical image analysis: A review
Padmavathi Kora, Chui Ping Ooi, Oliver Faust, et al.
Journal of Applied Biomedicine (2021) Vol. 42, Iss. 1, pp. 79-107
Closed Access | Times Cited: 243
Radiomics in Glioblastoma: Current Status and Challenges Facing Clinical Implementation
Ahmad Chaddad, Michael Jonathan Kucharczyk, Paul Daniel, et al.
Frontiers in Oncology (2019) Vol. 9
Open Access | Times Cited: 169
A Fully Automated Multimodal MRI-Based Multi-Task Learning for Glioma Segmentation and IDH Genotyping
Jianhong Cheng, Jin Liu, Hulin Kuang, et al.
IEEE Transactions on Medical Imaging (2022) Vol. 41, Iss. 6, pp. 1520-1532
Closed Access | Times Cited: 105
An overview of deep learning methods for multimodal medical data mining
Fatemeh Behrad, Mohammad Saniee Abadeh
Expert Systems with Applications (2022) Vol. 200, pp. 117006-117006
Closed Access | Times Cited: 103
Isocitrate dehydrogenase (IDH) status prediction in histopathology images of gliomas using deep learning
Sidong Liu, Zubair Shah, Aydın Sav, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 113
Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
Chenjie Ge, Irene Yu‐Hua Gu, Asgeir Store Jakola, et al.
IEEE Access (2020) Vol. 8, pp. 22560-22570
Open Access | Times Cited: 104
A new pyramidal concatenated CNN approach for environmental sound classification
Fatih Demir, Muammer Türkoğlu, Muzaffer Aslan, et al.
Applied Acoustics (2020) Vol. 170, pp. 107520-107520
Closed Access | Times Cited: 99
Optimizing Neuro-Oncology Imaging: A Review of Deep Learning Approaches for Glioma Imaging
Madeleine Shaver, Paul Kohanteb, Catherine Chiou, et al.
Cancers (2019) Vol. 11, Iss. 6, pp. 829-829
Open Access | Times Cited: 92
Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review
Quinlan D. Buchlak, Nazanin Esmaili, Jean‐Christophe Leveque, et al.
Journal of Clinical Neuroscience (2021) Vol. 89, pp. 177-198
Closed Access | Times Cited: 86
Artificial Intelligence in Imaging: The Radiologist’s Role
Daniel L. Rubin
Journal of the American College of Radiology (2019) Vol. 16, Iss. 9, pp. 1309-1317
Open Access | Times Cited: 82
Prediction of lower-grade glioma molecular subtypes using deep learning
Yutaka Matsui, Takashi Maruyama, Masayuki Nitta, et al.
Journal of Neuro-Oncology (2019) Vol. 146, Iss. 2, pp. 321-327
Closed Access | Times Cited: 81
Artificial intelligence radiogenomics for advancing precision and effectiveness in oncologic care (Review)
Eleftherios Trivizakis, Georgios Z. Papadakis, Ioannis Souglakos, et al.
International Journal of Oncology (2020) Vol. 57, Iss. 1, pp. 43-53
Open Access | Times Cited: 74
Fine-Grained Lung Cancer Classification from PET and CT Images Based on Multidimensional Attention Mechanism
Ruoxi Qin, Zhenzhen Wang, Lingyun Jiang, et al.
Complexity (2020) Vol. 2020, pp. 1-12
Open Access | Times Cited: 71
Diagnosis of brain diseases in fusion of neuroimaging modalities using deep learning: A review
Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, et al.
Information Fusion (2022) Vol. 93, pp. 85-117
Closed Access | Times Cited: 67
Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis
Anne Jian, Kevin Jang, Maurizio Manuguerra, et al.
Neurosurgery (2021) Vol. 89, Iss. 1, pp. 31-44
Closed Access | Times Cited: 59
Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework
Biswajit Jena, Sanjay Saxena, Gopal Krishna Nayak, et al.
Cancers (2022) Vol. 14, Iss. 16, pp. 4052-4052
Open Access | Times Cited: 52
Transfer Learning Approaches for Neuroimaging Analysis: A Scoping Review
Zaniar Ardalan, Vignesh Subbian
Frontiers in Artificial Intelligence (2022) Vol. 5
Open Access | Times Cited: 41
Deep Learning for MRI Segmentation and Molecular Subtyping in Glioblastoma: Critical Aspects from an Emerging Field
Marta Bonada, Luca Francesco Rossi, Giovanni Carone, et al.
Biomedicines (2024) Vol. 12, Iss. 8, pp. 1878-1878
Open Access | Times Cited: 11
Deep Learning AI Applications in the Imaging of Glioma
Avraham Zlochower, Daniel Chow, Peter Chang, et al.
Topics in Magnetic Resonance Imaging (2020) Vol. 29, Iss. 2, pp. 115-00
Closed Access | Times Cited: 70
Deep semi-supervised learning for brain tumor classification
Chenjie Ge, Irene Yu‐Hua Gu, Asgeir Store Jakola, et al.
BMC Medical Imaging (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 70
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: 67
Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning
Yiming Li, Dong Wei, Xing Liu, et al.
European Radiology (2021) Vol. 32, Iss. 2, pp. 747-758
Closed Access | Times Cited: 54
ViolenceNet: Dense Multi-Head Self-Attention with Bidirectional Convolutional LSTM for Detecting Violence
Fernando J. Rendón-Segador, Juan A. Álvarez-García, Fernando Enríquez, et al.
Electronics (2021) Vol. 10, Iss. 13, pp. 1601-1601
Open Access | Times Cited: 51
Convolutional neural network and its pretrained models for image classification and object detection: A survey
Biswajit Jena, Gopal Krishna Nayak, Sanjay Saxena
Concurrency and Computation Practice and Experience (2021) Vol. 34, Iss. 6
Closed Access | Times Cited: 45
Deep Learning Can Differentiate IDH-Mutant from IDH-Wild GBM
Luca Pasquini, Antonio Napolitano, Emanuela Tagliente, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 4, pp. 290-290
Open Access | Times Cited: 42
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