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:
Observing deep radiomics for the classification of glioma grades
Kazuma Kobayashi, Mototaka Miyake, Masamichi Takahashi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 38
Kazuma Kobayashi, Mototaka Miyake, Masamichi Takahashi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 38
Showing 26-50 of 38 citing articles:
In Vivo Quantitative Imaging of Glioma Heterogeneity Employing Positron Emission Tomography
Cristina Barca, Claudia Foray, Bastian Zinnhardt, et al.
Cancers (2022) Vol. 14, Iss. 13, pp. 3139-3139
Open Access | Times Cited: 4
Cristina Barca, Claudia Foray, Bastian Zinnhardt, et al.
Cancers (2022) Vol. 14, Iss. 13, pp. 3139-3139
Open Access | Times Cited: 4
RadiomicsJ: a library to compute radiomic features
Tatsuaki KOBAYASHI
Radiological Physics and Technology (2022) Vol. 15, Iss. 3, pp. 255-263
Closed Access | Times Cited: 4
Tatsuaki KOBAYASHI
Radiological Physics and Technology (2022) Vol. 15, Iss. 3, pp. 255-263
Closed Access | Times Cited: 4
Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment
Mateusz Garbulowski, Karolina Smolińska, Uğur Çabuk, et al.
Cancers (2022) Vol. 14, Iss. 4, pp. 1014-1014
Open Access | Times Cited: 3
Mateusz Garbulowski, Karolina Smolińska, Uğur Çabuk, et al.
Cancers (2022) Vol. 14, Iss. 4, pp. 1014-1014
Open Access | Times Cited: 3
Deep Radiomics: A Picture’s Worth a Thousand Words - A Review
Syeda Meraj, Asadullah Shah, A. H. Ismail, et al.
(2024), pp. 1-6
Closed Access
Syeda Meraj, Asadullah Shah, A. H. Ismail, et al.
(2024), pp. 1-6
Closed Access
Current status and future direction of cancer research using artificial intelligence for clinical application
Ryuji Hamamoto, Masaaki Komatsu, Masayoshi Yamada, et al.
Cancer Science (2024)
Open Access
Ryuji Hamamoto, Masaaki Komatsu, Masayoshi Yamada, et al.
Cancer Science (2024)
Open Access
Deep learning radiomics nomograms predict Isocitrate dehydrogenase (IDH) genotypes in brain glioma: A multicenter study
Darui Li, Wanjun Hu, Laiyang Ma, et al.
Magnetic Resonance Imaging (2024), pp. 110314-110314
Closed Access
Darui Li, Wanjun Hu, Laiyang Ma, et al.
Magnetic Resonance Imaging (2024), pp. 110314-110314
Closed Access
An Exploration of the Latent Space of a Convolutional Variational Autoencoder for the Generation of Musical Instrument Tones
Anastasia Natsiou, Seán O’Leary, Luca Longo
Communications in computer and information science (2023), pp. 470-486
Closed Access | Times Cited: 1
Anastasia Natsiou, Seán O’Leary, Luca Longo
Communications in computer and information science (2023), pp. 470-486
Closed Access | Times Cited: 1
Simplifying Radiomics Workflow for Predicting Grade of Glioma: An Approach for Rapid and Reproducible Radiomics
Yunus Soleymani, Peyman Sheikhzadeh, Mohammad Mohammadzadeh, et al.
Journal of Biomedical Physics and Engineering (2023) Vol. online
Open Access | Times Cited: 1
Yunus Soleymani, Peyman Sheikhzadeh, Mohammad Mohammadzadeh, et al.
Journal of Biomedical Physics and Engineering (2023) Vol. online
Open Access | Times Cited: 1
Discovering Digital Tumor Signatures—Using Latent Code Representations to Manipulate and Classify Liver Lesions
Jens Kleesiek, Benedikt Kersjes, Kai Ueltzhöffer, et al.
Cancers (2021) Vol. 13, Iss. 13, pp. 3108-3108
Open Access | Times Cited: 3
Jens Kleesiek, Benedikt Kersjes, Kai Ueltzhöffer, et al.
Cancers (2021) Vol. 13, Iss. 13, pp. 3108-3108
Open Access | Times Cited: 3
Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity
Eric P. Xing, Liangliang Liu, Xin Xing, et al.
2022 26th International Conference on Pattern Recognition (ICPR) (2022), pp. 2328-2334
Closed Access | Times Cited: 1
Eric P. Xing, Liangliang Liu, Xin Xing, et al.
2022 26th International Conference on Pattern Recognition (ICPR) (2022), pp. 2328-2334
Closed Access | Times Cited: 1
5. The Potential of Medical Image Analysis Technology in the Field of Cancer Treatment
Kazuma Kobayashi, Ryuji Hamamoto
Japanese Journal of Radiological Technology (2022) Vol. 78, Iss. 1, pp. 101-106
Closed Access
Kazuma Kobayashi, Ryuji Hamamoto
Japanese Journal of Radiological Technology (2022) Vol. 78, Iss. 1, pp. 101-106
Closed Access
Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space
Yunni Qu, David Yan, Eric P. Xing, et al.
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2022), pp. 3849-3853
Closed Access
Yunni Qu, David Yan, Eric P. Xing, et al.
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2022), pp. 3849-3853
Closed Access
Glioma grade prediction using a cross-fusion network based on unsegmented multi-sequence magnetic resonance images
Qijian Chen, Lihui Wang, Shunchao Guo, et al.
2022 16th IEEE International Conference on Signal Processing (ICSP) (2022), pp. 447-451
Closed Access
Qijian Chen, Lihui Wang, Shunchao Guo, et al.
2022 16th IEEE International Conference on Signal Processing (ICSP) (2022), pp. 447-451
Closed Access
