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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.

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Showing 1-25 of 120 citing articles:

An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in gliomas
Guanzhang Li, Lin Li, Yiming Li, et al.
Brain (2021) Vol. 145, Iss. 3, pp. 1151-1161
Open Access | Times Cited: 170
Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential
Xingping Zhang, Yanchun Zhang, Guijuan Zhang, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 109
Artificial intelligence in diagnostic and interventional radiology: Where are we now?
Tom Boeken, Jean Feydy, Augustin Lecler, et al.
Diagnostic and Interventional Imaging (2022) Vol. 104, Iss. 1, pp. 1-5
Open Access | Times Cited: 103
Artificial Intelligence, Augmented Reality, and Virtual Reality Advances and Applications in Interventional Radiology
Elizabeth Von Ende, Sean G. Ryan, Matthew A. Crain, et al.
Diagnostics (2023) Vol. 13, Iss. 5, pp. 892-892
Open Access | Times Cited: 45
Radiomics for the Prediction of Treatment Outcome and Survival in Patients With Colorectal Cancer: A Systematic Review
Frank J. T. Staal, Denise J. van der Reijd, Marjaneh Taghavi, et al.
Clinical Colorectal Cancer (2020) Vol. 20, Iss. 1, pp. 52-71
Open Access | Times Cited: 92
Radiomics of Liver Metastases: A Systematic Review
Francesco Fiz, Luca Viganò, Nicolò Gennaro, et al.
Cancers (2020) Vol. 12, Iss. 10, pp. 2881-2881
Open Access | Times Cited: 89
Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging
Lin Lü, Laurent Dercle, Binsheng Zhao, et al.
Nature Communications (2021) Vol. 12, Iss. 1
Open Access | Times Cited: 65
Radiomics in colorectal cancer patients
Riccardo Inchingolo, Cesare Maino, Roberto Cannella, et al.
World Journal of Gastroenterology (2023) Vol. 29, Iss. 19, pp. 2888-2904
Open Access | Times Cited: 26
Radiomics and liver: Where we are and where we are headed?
Cesare Maino, Federica Vernuccio, Roberto Cannella, et al.
European Journal of Radiology (2024) Vol. 171, pp. 111297-111297
Closed Access | Times Cited: 11
CT and MRI of pancreatic tumors: an update in the era of radiomics
Marion Bartoli, Maxime Barat, Anthony Dohan, et al.
Japanese Journal of Radiology (2020) Vol. 38, Iss. 12, pp. 1111-1124
Closed Access | Times Cited: 52
Texture analysis imaging “what a clinical radiologist needs to know”
Giuseppe Corrias, Giulio Micheletti, Luigi Barberini, et al.
European Journal of Radiology (2021) Vol. 146, pp. 110055-110055
Closed Access | Times Cited: 47
Radiomics and Radiogenomics in Evaluation of Colorectal Cancer Liver Metastasis
Yun Wang, Luyao Ma, Xiaoping Yin, et al.
Frontiers in Oncology (2022) Vol. 11
Open Access | Times Cited: 28
Predicting survival for hepatic arterial infusion chemotherapy of unresectable colorectal liver metastases: Radiomics analysis of pretreatment computed tomography
Peng Liu, Haitao Zhu, Hai-Bin Zhu, et al.
Journal of Translational Internal Medicine (2022) Vol. 10, Iss. 1, pp. 56-64
Open Access | Times Cited: 28
Deep radiomics-based fusion model for prediction of bevacizumab treatment response and outcome in patients with colorectal cancer liver metastases: a multicentre cohort study
Shizhao Zhou, Dazhen Sun, Wujian Mao, et al.
EClinicalMedicine (2023) Vol. 65, pp. 102271-102271
Open Access | Times Cited: 18
Evaluation of liver tumour response by imaging
Jules Grégory, Marco Dioguardi Burgio, Giuseppe Corrias, et al.
JHEP Reports (2020) Vol. 2, Iss. 3, pp. 100100-100100
Open Access | Times Cited: 48
Deep learning‐based radiomics predicts response to chemotherapy in colorectal liver metastases
Jingwei Wei, Cheng Jin, Dongsheng Gu, et al.
Medical Physics (2020) Vol. 48, Iss. 1, pp. 513-522
Closed Access | Times Cited: 47
Delta-Radiomics Predicts Response to First-Line Oxaliplatin-Based Chemotherapy in Colorectal Cancer Patients with Liver Metastases
Valentina Giannini, Laura Pusceddu, Arianna Defeudis, et al.
Cancers (2022) Vol. 14, Iss. 1, pp. 241-241
Open Access | Times Cited: 26
Prime Time for Artificial Intelligence in Interventional Radiology
Jarrel Seah, Tom Boeken, Marc Sapoval, et al.
CardioVascular and Interventional Radiology (2022) Vol. 45, Iss. 3, pp. 283-289
Open Access | Times Cited: 23
Deep learning‐based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer
Julius Keyl, René Hosch, Aaron Berger, et al.
Journal of Cachexia Sarcopenia and Muscle (2022) Vol. 14, Iss. 1, pp. 545-552
Open Access | Times Cited: 23
Digital Medical X-ray Imaging, CAD in Lung Cancer and Radiomics in Colorectal Cancer: Past, Present and Future
Jacobo Porto-Álvarez, Gary T. Barnes, Alex Villanueva, et al.
Applied Sciences (2023) Vol. 13, Iss. 4, pp. 2218-2218
Open Access | Times Cited: 14
Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment
Vincenza Granata, Roberta Fusco, Federica De Muzio, et al.
La radiologia medica (2023) Vol. 128, Iss. 11, pp. 1310-1332
Closed Access | Times Cited: 13
Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases
Y. Miyamoto, Takeshi Nakaura, Mayuko Ohuchi, et al.
Journal of the Anus Rectum and Colon (2025) Vol. 9, Iss. 1, pp. 117-126
Open Access
Radiomic imaging: Basic principles and applications
Francesco Pisu, Luca Saba
Elsevier eBooks (2025), pp. 225-248
Closed Access
The relevance of CT-based geometric and radiomics analysis of whole liver tumor burden to predict survival of patients with metastatic colorectal cancer
Alexander Mühlberg, Julian Walter Holch, Volker Heinemann, et al.
European Radiology (2020) Vol. 31, Iss. 2, pp. 834-846
Closed Access | Times Cited: 36
Impact of inter-reader contouring variability on textural radiomics of colorectal liver metastases
Francesco Rizzetto, Francesca Calderoni, C. De Mattia, et al.
European Radiology Experimental (2020) Vol. 4, Iss. 1
Open Access | Times Cited: 36
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