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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:

Classification of lung nodules based on CT images using squeeze-and-excitation network and aggregated residual transformations
Guobin Zhang, Zhiyong Yang, Li Gong, et al.
La radiologia medica (2020) Vol. 125, Iss. 4, pp. 374-383
Closed Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Deep Learning Applications in Computed Tomography Images for Pulmonary Nodule Detection and Diagnosis: A Review
Rui Li, Chuda Xiao, Yongzhi Huang, et al.
Diagnostics (2022) Vol. 12, Iss. 2, pp. 298-298
Open Access | Times Cited: 90
Effective lung nodule detection using deep CNN with dual attention mechanisms
Zia Urrehman, Yan Qiang, Long Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 20
Artificial Intelligence and COVID-19 Using Chest CT Scan and Chest X-ray Images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment
Roberta Fusco, Roberta Grassi, Vincenza Granata, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 10, pp. 993-993
Open Access | Times Cited: 75
Detection of lung nodule and cancer using novel Mask-3 FCM and TWEDLNN algorithms
Laxmikant Tiwari, Rohit Raja, Vineet Kumar Awasthi, et al.
Measurement (2020) Vol. 172, pp. 108882-108882
Closed Access | Times Cited: 64
Preliminary Report on Computed Tomography Radiomics Features as Biomarkers to Immunotherapy Selection in Lung Adenocarcinoma Patients
Vincenza Granata, Roberta Fusco, Matilde Costa, et al.
Cancers (2021) Vol. 13, Iss. 16, pp. 3992-3992
Open Access | Times Cited: 53
Towards Machine Learning-Aided Lung Cancer Clinical Routines: Approaches and Open Challenges
Francisco Silva, Tânia Pereira, Inês Neves, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 3, pp. 480-480
Open Access | Times Cited: 27
Classification Of Lung Cancer Using Lightweight Deep Neural Networks
Rashmi Mothkur, B. N. Veerappa
Procedia Computer Science (2023) Vol. 218, pp. 1869-1877
Open Access | Times Cited: 20
SE-ResNeXt-50-CNN: A Deep Learning Model for Lung Cancer Classification
Annu Priya, P. Shyamala Bharathi
Applied Soft Computing (2025), pp. 112696-112696
Closed Access
Application of radiomics in diagnosis and treatment of lung cancer
Feng Pan, Feng Li, Baocai Liu, et al.
Frontiers in Pharmacology (2023) Vol. 14
Open Access | Times Cited: 15
Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment
Valerio Nardone, Luca Boldrini, Roberta Grassi, et al.
Cancers (2021) Vol. 13, Iss. 14, pp. 3590-3590
Open Access | Times Cited: 29
Lung Cancer Classification Using Squeeze and Excitation Convolutional Neural Networks with Grad Cam++ Class Activation Function
Eali Stephen Neal Joshua, Debnath Bhattacharyya, Midhun Chakkravarthy, et al.
Traitement du signal (2021) Vol. 38, Iss. 4, pp. 1103-1112
Open Access | Times Cited: 29
An improved SqueezeNet model for the diagnosis of lung cancer in CT scans
Michail Tsivgoulis, Θωμάς Παπαστεργίου, V. Megalooikonomou
Machine Learning with Applications (2022) Vol. 10, pp. 100399-100399
Open Access | Times Cited: 21
Self-supervised transfer learning framework driven by visual attention for benign–malignant lung nodule classification on chest CT
Ruoyu Wu, Changyu Liang, Yuan Li, et al.
Expert Systems with Applications (2022) Vol. 215, pp. 119339-119339
Closed Access | Times Cited: 21
A federated learning framework for pneumonia image detection using distributed data
Amer Kareem, Haiming Liu, Vladan Velisavljević
Healthcare Analytics (2023) Vol. 4, pp. 100204-100204
Open Access | Times Cited: 10
Pulmonary Nodule Classification Using a Multiview Residual Selective Kernel Network
Herng-Hua Chang, Cheng-Zhe Wu, Audrey Haihong Gallogly
Deleted Journal (2024) Vol. 37, Iss. 1, pp. 347-362
Open Access | Times Cited: 3
Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model
Yiwei Tong, Zhaoyu Hu, Haoyu Wang, et al.
European Radiology (2024) Vol. 34, Iss. 8, pp. 5477-5486
Open Access | Times Cited: 3
Adaptive Aggregated Attention Network for Pulmonary Nodule Classification
Kai Xia, Jianning Chi, Yuan Gao, et al.
Applied Sciences (2021) Vol. 11, Iss. 2, pp. 610-610
Open Access | Times Cited: 24
Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when
Vincenza Granata, Roberta Fusco, Andrea Belli, et al.
Infectious Agents and Cancer (2022) Vol. 17, Iss. 1
Open Access | Times Cited: 17
Spatial attention-based residual network for human burn identification and classification
Dhirendra Prasad Yadav, Turki Aljrees, Deepak Kumar, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 9
Lung Cancer Imaging: Screening Result and Nodule Management
Susanna Guerrini, Davide Del Roscio, Matteo Zanoni, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 4, pp. 2460-2460
Open Access | Times Cited: 14
Ada-GridRF: A Fast and Automated Adaptive Boost Based Grid Search Optimized Random Forest Ensemble model for Lung Cancer Detection
Ananya Bhattacharjee, R. Murugan, Badal Soni, et al.
Physical and Engineering Sciences in Medicine (2022) Vol. 45, Iss. 3, pp. 981-994
Closed Access | Times Cited: 12
An improved 3-D attention CNN with hybrid loss and feature fusion for pulmonary nodule classification
Yao‐Sian Huang, Teh-Chen Wang, Shengzhi Huang, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 229, pp. 107278-107278
Closed Access | Times Cited: 12
Computed Tomography Structured Reporting in the Staging of Lymphoma: A Delphi Consensus Proposal
Vincenza Granata, Silvia Pradella, Diletta Cozzi, et al.
Journal of Clinical Medicine (2021) Vol. 10, Iss. 17, pp. 4007-4007
Open Access | Times Cited: 17
Structured Reporting of Lung Cancer Staging: A Consensus Proposal
Vincenza Granata, Roberto Grassi, Vittorio Miele, et al.
Diagnostics (2021) Vol. 11, Iss. 9, pp. 1569-1569
Open Access | Times Cited: 16
PB-LNet: a model for predicting pathological subtypes of pulmonary nodules on CT images
Yuchong Zhang, Hui Qu, Yumeng Tian, et al.
BMC Cancer (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 6
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